Time Series

ARIMA

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Associated Constructors

Time Series

Syntax: Time Series( Y( column ) )

Description: Models a series of observations over equally spaced time points. Includes a time series plot, autocorrelations, variogram, spectral density, ARIMA, seasonal ARIMA, smoothing models, and forecasts.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );

Columns

By

Syntax: obj << By( column(s) )

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );

Input List

Syntax: obj << Input List( column(s) )

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );

Time ID

Syntax: obj << Time ID( column )

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );

X

Syntax: obj << X( column )

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );

Y

Syntax: obj << Y( column(s) )

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );

Item Messages

AR Coefficients

Syntax: obj << AR Coefficients( state=0|1 )

Description: Displays or hides the autocorrelation coefficient plot.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << AR Coefficients( 1 );

ARIMA

Syntax: obj << ARIMA( p, d, q, <No Intercept( 0|1 )>, <No Constrain( 0|1 )>, <Confidence Intervals( level )> )

Description: Fits an ARIMA model. Set order p,d, and q for an ARIMA(p,d,q) model. Set level for values other than 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << arima( 1, 0, 0, No Intercept( 1 ), No Constrain( 1 ), Confidence Intervals( 0.99 ) );

ARIMA Model Group

Syntax: obj << ARIMA Model Group( AR(p0,p1),Diff(d0,d1),MA(q0,q1),Seasonal AR(P0,P1),Seasonal Diff(D0,D1),Seasonal MA(Q0,Q1),Seasonal Period(S0,S1),Confidence Intervals(C),Intercept(1),Constrain fit(1) )

Description: Fit a set of ARIMA models whose orders are in specified ranges.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << ARIMA Model Group( AR( 0, 2 ), MA( 0, 2 ) );

Autocorrelation

Syntax: obj << Autocorrelation( state=0|1 )

Description: Displays or hides the autocorrelation plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Autocorrelation( 1 );

Autocorrelation Lags

Syntax: obj = Time Series(...Autocorrelation Lags( number=25 )...)

Description: Set launch option for the maximum number of periods between points used in computing autocorrelations. "25" by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ), Autocorrelation Lags( 10 ) );

Combine and Save Forecasts from Models

Syntax: obj << Combine and Save Forecasts from Models

Description: Creates a new data table with the combined results from all model fits in the report.

JMP Version Added: 16

Connecting Lines

Syntax: obj << Connecting Lines( state=0|1 )

Description: Displays or hides connected lines in the basic time series plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Connecting Lines( 1 );

Cross Correlation

Syntax: obj << Cross Correlation( state=0|1 )

Description: Displays or hides the cross correlation plot.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = dt << Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Cross Correlation( 1 );

Damped-Trend Linear Exponential Smoothing

Syntax: obj << Damped-Trend Linear Exponential Smoothing( Zero to One|Unconstrained|Stable Invertible|Custom( (Damping|Level)( Unconstrained| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Fits a damped trend smoothing model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    "Damped-Trend Linear Exponential Smoothing"n( Zero to One )
);

Difference

Syntax: obj << Difference( d, <D>, <S> )

Description: Computes the differenced series and produces graphs of the autocorrelations and partial autocorrelations of the differenced series. The differenced series is given by (1-B)^d * (1-B^S)^D * y_t , where y_t is the time series, B is the backshift operator defined by B * y_t = y_(t-1), d is the nonseasonal differencing order, D is the seasonal differencing order, and S is the number of observations per period.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Difference( 1 );
obj << Difference( 1, 1, 12 );

Double Exponential Smoothing

Syntax: obj << Double Exponential Smoothing( Zero to One|Unconstrained|Stable Invertible|Custom( Level( Unconstrained| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Invoke fitting a double exponential smoothing model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    Double Exponential Smoothing( Zero to One ),
    Double Exponential Smoothing( Unconstrained ),
    Double Exponential Smoothing( Stable Invertible ),
    Double Exponential Smoothing( Custom( Level( Bounded( 0.8, 1 ) ) ) ),
    Double Exponential Smoothing( Custom( Level( Fixed( 0 ) ) ) ),
    Double Exponential Smoothing( Custom( Level( Unconstrained ) ) )
);

Fit Recommended ETS

Syntax: obj << Fit Recommended ETS( Period( m ),Constrained( "Yes"|"No" ) )

Description: Fits all recommended state space smoothing models.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Passengers ) );
obj << Fit Recommended ETS( Period( 12 ), Constrained( "Yes" ) );

Forecast Periods

Syntax: obj = Time Series(...Forecast Periods( number=25 )...)

Description: Set launch option for the number of steps ahead in forecasting report. "25" by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ), Forecast Periods( 10 ) );
obj << ARIMA( 1, 0, 0 );

Forecast on Holdback

Syntax: obj = Time Series(...Forecast on Holdback( state=0|1 )...)

Description: Determines whether the forecasts are made on future observations or on the holdback observations. If this option is selected, the forecasts are made on the holdback set that is determined by the number specified in the Forecast Periods option.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ), Forecast on Holdback( 1 ) );
obj << arima( 1, 0, 0 );
obj << Number of Forecast Periods( 100 );

Generate Simulation

Syntax: obj << Generate Simulation( id, seed, length, n )

Description: Generates a data table of multiple future trajectories of a fitted model. Returns the table reference.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
dt = obj << Generate Simulation( 1, 11111, 100, 5 );

Get Model Specs

Syntax: obj << Get Model Specs

Description: Returns a named list of model results, each of which is named by model specification. Included in the output are estimates and standard errors. Available for ARIMA, Seasonal ARIMA, all smoothing models and Transfer Function Models.

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Log Passengers ) );
obj << Seasonal ARIMA( 0, 1, 1, 0, 1, 1, 12, No Intercept( 1 ) );
l = obj << Get Model Specs;
Show( l );

Get Models

Syntax: obj << Get Models

Description: Returns a named list of model results, each of which is named by model descriptions. Included in the output are estimates and standard errors. Available for ARIMA, Seasonal ARIMA, all smoothing models and Transfer Function Models.

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Log Passengers ) );
obj << Seasonal ARIMA( 0, 1, 1, 0, 1, 1, 12, No Intercept( 1 ) );
l = obj << Get Models;
Show( l );

Hide All Reports

Syntax: obj << Hide All Reports

Description: Hides all of the models that are listed in the Model Comparison table from the report window.

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Passengers ) );
obj << Fit Recommended ETS( Period( 12 ), Constrained( "Yes" ) );
obj << Hide All Model Reports;

Input Series

Syntax: obj << Input Series( Column, <ARIMA( )>| <Prewhitening( )> ... )

Description: Groups messages sent to the input series. Note: requires an Input List variable be specified.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = dt << Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Input Series( :Input Gas Rate, ARIMA( 1, 0, 0 ) );

Keep Best Models

Syntax: obj << Keep Best Models( "AIC"|"SBC" )

Description: Retains the best models among individual model classes and removes the remaining models.

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Passengers ) );
obj << Fit Recommended ETS( Period( 12 ), Constrained( "Yes" ) );
Wait( 1 );
obj << Keep Best Models( "AIC" );

Lambda for Box-Cox

Syntax: obj = Time Series(...Lambda for Box-Cox( number=0 )...)

Description: Specifies the lambda parameter used for the Box-Cox transformation of the original data. "0" by default.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series(
    Y( :Steel Shipments ),
    Name( "Use Box-Cox Transformation" )(1),
    Name( "Lambda for Box-Cox" )(0)
);
obj << arima( 1, 0, 0 );
obj << Number of Forecast Periods( 100 );

Linear Exponential Smoothing

Syntax: obj << Linear Exponential Smoothing( Zero to One|Unconstrained|Stable Invertible|Custom( (Trend|Level)( Unconstrained| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Fits a linear exponential smoothing model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    Linear Exponential Smoothing( Zero to One ),
    Linear Exponential Smoothing( Unconstrained ),
    Linear Exponential Smoothing( Stable Invertible ),
    Linear Exponential Smoothing(
        Custom( Level( Bounded( 0.8, 1 ) ), Trend( Bounded( 0.7, 0.9 ) ) )
    ),
    Linear Exponential Smoothing( Custom( Level( Fixed( 0 ) ), Trend( Fixed( .3 ) ) ) ),
    Linear Exponential Smoothing( Custom( Level( Unconstrained ), Trend( Fixed( .4 ) ) ) )
);

Maximum Iterations

Syntax: obj << Maximum Iterations( maxIter=250 )

Description: Reset the maximum number of iterations for future optimizations used in ARIMA model fitting. "250" by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Maximum Iterations( 2 );
obj << ARIMA( 1, 0, 0 );

Mean Line

Syntax: obj << Mean Line( state=0|1 )

Description: Displays or hides the mean line in the basic time series plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Mean Line( 1 );

Model Comparison Report

Syntax: obj << Model Comparison Report

Description: Configures the Model Comparison report settings.

Number of Forecast Periods

Syntax: obj << Number of Forecast Periods( number )

Description: Resets the number of forecast periods and updates the forecasting report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << Number of Forecast Periods( 100 );

Partial Autocorrelation

Syntax: obj << Partial Autocorrelation( state=0|1 )

Description: Displays or hides the partial autocorrelation plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Partial Autocorrelation( 1 );

Prewhitening

Syntax: obj << Prewhitening( Order(p, d, q), Seasonal(P, D, Q, S) )

Description: Sets the prewhitening order.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = dt << Time Series(
    Y( :Output CO2 ),
    Input List( :Input Gas Rate ),
    Input Series(
        :Input Gas Rate,
        Prewhitening( Order( 1, 0, 0 ), Seasonal( 0, 0, 0, 12 ) )
    )
);

Remove All Simulation

Syntax: obj << Remove All Simulation

Description: Removes all simulated future trajectories.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << arima( 2, 0, 0 );
obj << Simulate More( 1, 2 );
obj << Simulate More( 2, 3 );
obj << Remove All Simulation;

Remove Cycle

Syntax: obj << Remove Cycle( Units per Cycle( number ), Has Constant( 0|1 ) )

Description: Estimates the cyclic component using a cosine function and then removes it from the data.

dt = Open( "$SAMPLE_DATA/Time Series/Monthly Sales.jmp" );
obj = dt << Time Series( Y( :Sales ) );
obj << Remove Cycle( Units per Cycle( 12 ), Has Constant( 1 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Remove Linear Trend

Syntax: obj << Remove Linear Trend

Description: Estimates the linear trend and then removes it from the data.

dt = Open( "$SAMPLE_DATA/Time Series/Monthly Sales.jmp" );
obj = dt << Time Series( Y( :Sales ) );
obj << Remove Linear Trend;

Remove Model Simulation

Syntax: obj << Remove Model Simulation( id )

Description: Removes simulated future trajectories of a fitted model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << arima( 2, 0, 0 );
obj << Simulate More( 1, 2 );
obj << Simulate More( 2, 3 );
obj << Remove Model Simulation( 1 );

Save Spectral Density

Syntax: obj << Save Spectral Density

Description: Save spectral density to a table.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Save Spectral Density;

Seasonal ARIMA

Syntax: obj << Seasonal ARIMA( p, d, q, P, D, Q, S, <No Intercept( 0|1 )>, <No Constrain( 0|1 )>, <Confidence Intervals( level )> )

Description: Fits a seasonal ARIMA model. Set order p,d,q,P,D,Q,and S for an ARIMA(p,d,q)(P,D,Q)S model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << seasonal arima( 1, 0, 0, 1, 0, 0, 12 );
obj << seasonal arima(
    1,
    0,
    0,
    1,
    0,
    0,
    12,
    No Intercept( 1 ),
    No Constrain( 1 ),
    Confidence Intervals( 0.99 )
);

Seasonal Exponential Smoothing

Syntax: obj << Seasonal Exponential Smoothing( Zero to One|Unconstrained|Custom( (Level| Seasonal)( Unconstrained| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Fits a seasonal exponential smoothing model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    Seasonal Exponential Smoothing(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Seasonal( Bounded( 0, 1 ) ) )
    )
);

Set Seed

Syntax: obj << Set Seed( seed )

Description: Sets random seed.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << Set Seed( 1111 );
obj << Simulate Once( 1 );
obj << Set Seed( 1111 );
obj << Simulate Once( 1 );

Show Box-Cox Transformation Plot

Syntax: obj << Show Box-Cox Transformation Plot( state=0|1 )

JMP Version Added: 16

Show Lag Plot

Syntax: obj << Show Lag Plot( state=0|1 )

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Displays or hides points in the basic time series plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Show Points( 1 );

Simple Exponential Smoothing

Syntax: obj << Simple Exponential Smoothing( Zero to One|Unconstrained|Stable Invertible|Custom( Level( Unconstrained| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Fits a simple exponential smoothing model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    Simple Exponential Smoothing( Zero to One ),
    Simple Exponential Smoothing( Unconstrained ),
    Simple Exponential Smoothing( Stable Invertible ),
    Simple Exponential Smoothing( Custom( Level( Bounded( 0.8, 1 ) ) ) ),
    Simple Exponential Smoothing( Custom( Level( Fixed( 0 ) ) ) ),
    Simple Exponential Smoothing( Custom( Level( Unconstrained ) ) )
);

Simple Moving Average

Syntax: obj << Simple Moving Average

Description: Invoke a simple moving average specification dialog and fit a model, if there are no additional arguments. Pass arguments to the simple moving average model scriptable. Return value is the simple moving average model scriptable handle. See Simple Moving Average scriptable for arguments details.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = dt << Time Series( Y( :Close ) );
sma = obj << Simple Moving Average;
sma << Add Model( 10 );

Simple Moving Average Centering Method

Syntax: obj << Simple Moving Average Centering Method( "No Centering"|"Centered"|"Centered and Double Smoothed for Even Number of Terms" )

Simulate More

Syntax: obj << Simulate More( id, n )

Description: Simulates multiple future trajectories of a fitted model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << arima( 2, 0, 0 );
obj << Simulate More( 1, 2 );
obj << Simulate More( 2, 3 );

Simulate Once

Syntax: obj << Simulate Once( id )

Description: Simulates one future trajectory of a fitted model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << arima( 1, 0, 0 );
obj << arima( 2, 0, 0 );
obj << Simulate Once( 1 );
obj << Simulate Once( 2 );

Spectral Density

Syntax: obj << Spectral Density( state=0|1 )

Description: Displays or hides the spectral density graphs.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Spectral Density( 1 );

State Space Smoothing

Syntax: obj << State Space Smoothing( Error Type( "Additive"|"Multiplicative" ),Trend Type( "None"|"Additive"|"Multiplicative" ),Seasonal Type( "None"|"Additive"|"Multiplicative" ),Damped( "Yes"|"No" ),Period( m ),Constrained( "Yes"|"No" ) )

Description: Fits a state space smoothing model.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Time Series/Seriesg.jmp" );
obj = dt << Time Series( Y( :Passengers ) );
obj << State Space Smoothing(
    Error Type( "Multiplicative" ),
    Trend Type( "Additive" ),
    Seasonal Type( "Multiplicative" ),
    Damped( "No" ),
    Period( 12 ),
    Constrained( "Yes" )
);

Time Series Graph

Syntax: obj << Time Series Graph( state=0|1 )

Description: Turn on or off the basic time series plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Time Series Graph( 1 );

Transfer Function

Syntax: obj << Transfer Function( Order(p, d, q), Seasonal(P, D, Q, S), input1(Order(p, d, q), Seasonal(P, D, Q, S), Lag(lag)), <input2(Order(p, d, q), Seasonal(P, D, Q, S), Lag(lag))>, ..., <No Intercept(flag1)>, <No Constrain(flag2)>, <Alternative Parameterization( flag3 )>, <Confidence Intervals( level )>, <Number of Forecast Periods( nAhead )> )

Description: Fits a Transfer Function model.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = dt << Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    No Intercept( 1 ),
    Alternative Parameterization( 1 ),
    Confidence Intervals( 0.99 ),
    Number of Forecast Periods( 10 )
);

Use Box-Cox Transformation

Syntax: obj = Time Series(...Use Box-Cox Transformation( state=0|1 )...)

Description: Transforms the original data using a Box-Cox transformation with the lambda that is specified in the Lambda for Box-Cox option. If this option is selected, all analyses in the Time Series report are performed on the transformed data.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ), Name( "Use Box-Cox Transformation" )(1) );
obj << arima( 1, 0, 0 );
obj << Number of Forecast Periods( 100 );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the variogram plot in the Time Series Basic Diagnostics report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :Steel Shipments ) );
obj << Variogram( 1 );

Winters Method

Syntax: obj << Winters Method( Zero to One|Unconstrained|Custom( (Level|Seasonal|Trend)( Unconstrained| Seasonal| Bounded( lower, upper )| Fixed( value ) )), <Confidence Intervals(level)> )

Description: Fits a smoothing model using Winter's method.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom(
            Level( Bounded( 0, 1 ) ),
            Trend( Bounded( 0, 1 ) ),
            Seasonal( Bounded( 0, 1 ) )
        )
    )
);

X11

Syntax: obj << X11( Additive|Multiplicative )

Description: Removes trend and seasonal effects using the X-11 method developed by the US Bureau of the Census.

dt = Open( "$SAMPLE_DATA/Time Series/Monthly Sales.jmp" );
obj = dt << Time Series( X( :Date ), Y( :Sales ) );
obj << X11( Additive );

Shared Item Messages

Action

Syntax: obj << Action

Description: All-purpose trapdoor within a platform to insert expressions to evaluate. Temporarily sets the DisplayBox and DataTable contexts to the Platform.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Bivariate(
    Y( :height ),
    X( :weight ),
    Action( Distribution( Y( :height, :weight ), Histograms Only ) )
);

Apply Preset

Syntax: Apply Preset( preset ); Apply Preset( source, label, <Folder( folder {, folder2, ...} )> )

Description: Apply a previously created preset to the object, updating the options and customizations to match the saved settings.

JMP Version Added: 18

Anonymous preset

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ), t Test( 1 ) );
preset = obj << New Preset();
dt2 = Open( "$SAMPLE_DATA/Dogs.jmp" );
obj2 = dt2 << Oneway( Y( :LogHist0 ), X( :drug ) );
Wait( 1 );
obj2 << Apply Preset( preset );

Search by name

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ) );
Wait( 1 );
obj << Apply Preset( "Sample Presets", "Compare Distributions" );

Search within folder(s)

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ) );
Wait( 1 );
obj << Apply Preset( "Sample Presets", "t-Tests", Folder( "Compare Means" ) );

Automatic Recalc

Syntax: obj << Automatic Recalc( state=0|1 )

Description: Redoes the analysis automatically for exclude and data changes. If the Automatic Recalc option is turned on, you should consider using Wait(0) commands to ensure that the exclude and data changes take effect before the recalculation.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Automatic Recalc( 1 );
dt << Select Rows( 5 ) << Exclude( 1 );

Broadcast

Syntax: obj << Broadcast(message)

Description: Broadcasts a message to a platform. If return results from individual objects are tables, they are concatenated if possible, and the final format is identical to either the result from the Save Combined Table option in a Table Box or the result from the Concatenate option using a Source column. Other than those, results are stored in a list and returned.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Quality Control/Diameter.jmp" );
objs = Control Chart Builder(
    Variables( Subgroup( :DAY ), Y( :DIAMETER ) ),
    By( :OPERATOR )
);
objs[1] << Broadcast( Save Summaries );

Column Switcher

Syntax: obj << Column Switcher(column reference, {column reference, ...}, < Title(title) >, < Close Outline(0|1) >, < Retain Axis Settings(0|1) >, < Layout(0|1) >)

Description: Adds a control panel for changing the platform's variables

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
obj = dt << Contingency( Y( :size ), X( :marital status ) );
ColumnSwitcherObject = obj << Column Switcher(
    :marital status,
    {:sex, :country, :marital status}
);

Copy ByGroup Script

Syntax: obj << Copy ByGroup Script

Description: Create a JSL script to produce this analysis, and put it on the clipboard.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Copy ByGroup Script;

Copy Script

Syntax: obj << Copy Script

Description: Create a JSL script to produce this analysis, and put it on the clipboard.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Copy Script;

Data Table Window

Syntax: obj << Data Table Window

Description: Move the data table window for this analysis to the front.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Data Table Window;

Get By Levels

Syntax: obj << Get By Levels

Description: Returns an associative array mapping the by group columns to their values.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( X( :height ), Y( :weight ), By( :sex ) );
biv << Get By Levels;

Get ByGroup Script

Syntax: obj << Get ByGroup Script

Description: Creates a script (JSL) to produce this analysis and returns it as an expression.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
t = obj[1] << Get ByGroup Script;
Show( t );

Get Container

Syntax: obj << Get Container

Description: Returns a reference to the container box that holds the content for the object.

General

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
t = obj << Get Container;
Show( (t << XPath( "//OutlineBox" )) << Get Title );

Platform with Filter

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :age, :sex, :height ),
            Where( :age == {12, 13, 14} ),
            Where( :sex == "F" ),
            Where( :height >= 55 ),
            Display( :age, N Items( 6 ) )
        )
    )
);
New Window( "platform boxes",
    H List Box(
        Outline Box( "Report(platform)", Report( gb ) << Get Picture ),
        Outline Box( "platform << Get Container", (gb << Get Container) << Get Picture )
    )
);

Get Data Table

Syntax: obj << Get Data Table

Description: Returns a reference to the data table.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
t = obj << Get Datatable;
Show( N Rows( t ) );

Get Group Platform

Syntax: obj << Get Group Platform

Description: Return the Group Platform object if this platform is part of a Group. Otherwise, returns Empty().

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( Y( :weight ), X( :height ), By( :sex ) );
group = biv[1] << Get Group Platform;
Wait( 1 );
group << Layout( "Arrange in Tabs" );

Get Script

Syntax: obj << Get Script

Description: Creates a script (JSL) to produce this analysis and returns it as an expression.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
t = obj << Get Script;
Show( t );

Get Script With Data Table

Syntax: obj << Get Script With Data Table

Description: Creates a script(JSL) to produce this analysis specifically referencing this data table and returns it as an expression.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
t = obj << Get Script With Data Table;
Show( t );

Get Timing

Syntax: obj << Get Timing

Description: Times the platform launch.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
t = obj << Get Timing;
Show( t );

Get Web Support

Syntax: obj << Get Web Support

Description: Return a number indicating the level of Interactive HTML support for the display object. 1 means some or all elements are supported. 0 means no support.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Bivariate( Y( :Weight ), X( :Height ) );
s = obj << Get Web Support();
Show( s );

Get Where Expr

Syntax: obj << Get Where Expr

Description: Returns the Where expression for the data subset, if the platform was launched with By() or Where(). Otherwise, returns Empty()

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( X( :height ), Y( :weight ), By( :sex ) );
biv2 = dt << Bivariate( X( :height ), Y( :weight ), Where( :age < 14 & :height > 60 ) );
Show( biv[1] << Get Where Expr, biv2 << Get Where Expr );

Ignore Platform Preferences

Syntax: Ignore Platform Preferences( state=0|1 )

Description: Ignores the current settings of the platform's preferences. The message is ignored when sent to the platform after creation.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Bivariate(
    Ignore Platform Preferences( 1 ),
    Y( :height ),
    X( :weight ),
    Action( Distribution( Y( :height, :weight ), Histograms Only ) )
);

Local Data Filter

Syntax: obj << Local Data Filter

Description: To filter data to specific groups or ranges, but local to this platform

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
dt << Distribution(
    Nominal Distribution( Column( :country ) ),
    Local Data Filter(
        Add Filter( columns( :sex ), Where( :sex == "Female" ) ),
        Mode( Show( 1 ), Include( 1 ) )
    )
);

New JSL Preset

Syntax: New JSL Preset( preset )

Description: For testing purposes, create a preset directly from a JSL expression. Like <<New Preset, it will return a Platform Preset that can be applied using <<Apply Preset. But it allows you to specify the full JSL expression for the preset to test outside of normal operation. You will get an Assert on apply if the platform names do not match, but that is expected.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :Height ), X( :Age ) );
preset = obj << New JSL Preset( Oneway( Y( :A ), X( :B ), Each Pair( 1 ) ) );
Wait( 1 );
obj << Apply Preset( preset );

New Preset

Syntax: obj = New Preset()

Description: Create an anonymous preset representing the options and customizations applied to the object. This object can be passed to Apply Preset to copy the settings to another object of the same type.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ), t Test( 1 ) );
preset = obj << New Preset();

Paste Local Data Filter

Syntax: obj << Paste Local Data Filter

Description: Apply the local data filter from the clipboard to the current report.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
dist = Distribution( Continuous Distribution( Column( :POP ) ) );
filter = dist << Local Data Filter(
    Add Filter( columns( :Region ), Where( :Region == "MW" ) )
);
filter << Copy Local Data Filter;
dist2 = Distribution( Continuous Distribution( Column( :Lead ) ) );
Wait( 1 );
dist2 << Paste Local Data Filter;

Redo Analysis

Syntax: obj << Redo Analysis

Description: Rerun this same analysis in a new window. The analysis will be different if the data has changed.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Redo Analysis;

Redo ByGroup Analysis

Syntax: obj << Redo ByGroup Analysis

Description: Rerun this same analysis in a new window. The analysis will be different if the data has changed.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Redo ByGroup Analysis;

Relaunch Analysis

Syntax: obj << Relaunch Analysis

Description: Opens the platform launch window and recalls the settings that were used to create the report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Relaunch Analysis;

Relaunch ByGroup

Syntax: obj << Relaunch ByGroup

Description: Opens the platform launch window and recalls the settings that were used to create the report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Relaunch ByGroup;

Remove Column Switcher

Syntax: obj << Remove Column Switcher

Description: Removes the most recent Column Switcher that has been added to the platform.

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
obj = dt << Contingency( Y( :size ), X( :marital status ) );
ColumnSwitcherObject = obj << Column Switcher(
    :marital status,
    {:sex, :country, :marital status}
);
Wait( 2 );
obj << Remove Column Switcher;

Remove Local Data Filter

Syntax: obj << Remove Local Data Filter

Description: If a local data filter has been created, this removes it and restores the platform to use all the data in the data table directly

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
dist = dt << Distribution(
    Nominal Distribution( Column( :country ) ),
    Local Data Filter(
        Add Filter( columns( :sex ), Where( :sex == "Female" ) ),
        Mode( Show( 1 ), Include( 1 ) )
    )
);
Wait( 2 );
dist << remove local data filter;

Render Preset

Syntax: Render Preset( preset )

Description: For testing purposes, show the platform rerun script that would be used when applying a platform preset to the platform in the log. No changes are made to the platform.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :Height ), X( :Age ) );
obj << Render Preset( Expr( Oneway( Y( :A ), X( :B ), Each Pair( 1 ) ) ) );

Report

Syntax: obj << Report;Report( obj )

Description: Returns a reference to the report object.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
r = obj << Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

Report View

Syntax: obj << Report View( "Full"|"Summary" )

Description: The report view determines the level of detail visible in a platform report. Full shows all of the detail, while Summary shows only select content, dependent on the platform. For customized behavior, display boxes support a <<Set Summary Behavior message.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Report View( "Summary" );

Save ByGroup Script to Data Table

Syntax: Save ByGroup Script to Data Table( <name>, < <<Append Suffix(0|1)>, < <<Prompt(0|1)>, < <<Replace(0|1)> );

Description: Creates a JSL script to produce this analysis, and save it as a table property in the data table. You can specify a name for the script. The Append Suffix option appends a numeric suffix to the script name, which differentiates the script from an existing script with the same name. The Prompt option prompts the user to specify a script name. The Replace option replaces an existing script with the same name.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Save ByGroup Script to Data Table;

Save ByGroup Script to Journal

Syntax: obj << Save ByGroup Script to Journal

Description: Create a JSL script to produce this analysis, and add a Button to the journal containing this script.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Save ByGroup Script to Journal;

Save ByGroup Script to Script Window

Syntax: obj << Save ByGroup Script to Script Window

Description: Create a JSL script to produce this analysis, and append it to the current Script text window.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Save ByGroup Script to Script Window;

Save Script for All Objects

Syntax: obj << Save Script for All Objects

Description: Creates a script for all report objects in the window and appends it to the current Script window. This option is useful when you have multiple reports in the window.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Save Script for All Objects;

Save Script for All Objects To Data Table

Syntax: obj << Save Script for All Objects To Data Table( <name> )

Description: Saves a script for all report objects to the current data table. This option is useful when you have multiple reports in the window. The script is named after the first platform unless you specify the script name in quotes.

Example 1

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Save Script for All Objects To Data Table;

Example 2

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Time Series( Y( :steel shipments ), By( _bycol ) );
obj[1] << Save Script for All Objects To Data Table( "My Script" );

Save Script to Data Table

Syntax: Save Script to Data Table( <name>, < <<Prompt(0|1)>, < <<Replace(0|1)> );

Description: Create a JSL script to produce this analysis, and save it as a table property in the data table.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Save Script to Data Table( "My Analysis", <<Prompt( 0 ), <<Replace( 0 ) );

Save Script to Journal

Syntax: obj << Save Script to Journal

Description: Create a JSL script to produce this analysis, and add a Button to the journal containing this script.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Save Script to Journal;

Save Script to Report

Syntax: obj << Save Script to Report

Description: Create a JSL script to produce this analysis, and show it in the report itself. Useful to preserve a printed record of what was done.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Save Script to Report;

Save Script to Script Window

Syntax: obj << Save Script to Script Window

Description: Create a JSL script to produce this analysis, and append it to the current Script text window.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Save Script to Script Window;

SendToByGroup

Syntax: SendToByGroup( {":Column == level"}, command );

Description: Sends platform commands or display customization commands to each level of a by-group.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    By( :Sex ),
    SendToByGroup(
        {:sex == "F"},
        Continuous Distribution( Column( :weight ), Normal Quantile Plot( 1 ) )
    ),
    SendToByGroup( {:sex == "M"}, Continuous Distribution( Column( :weight ) ) )
);

SendToEmbeddedScriptable

Syntax: SendToEmbeddedScriptable( Dispatch( "Outline name", "Element name", command );

Description: SendToEmbeddedScriptable restores settings of embedded scriptable objects.

dt = Open( "$SAMPLE_DATA/Reliability/Fan.jmp" );
dt << Life Distribution(
    Y( :Time ),
    Censor( :Censor ),
    Censor Code( 1 ),
    <<Fit Weibull,
    SendToEmbeddedScriptable(
        Dispatch(
            {"Statistics", "Parametric Estimate - Weibull", "Profilers", "Density Profiler"},
            {1, Confidence Intervals( 0 ), Term Value( Time( 6000, Lock( 0 ), Show( 1 ) ) )}
        )
    )
);

SendToReport

Syntax: SendToReport( Dispatch( "Outline name", "Element name", Element type, command );

Description: Send To Report is used in tandem with the Dispatch command to customize the appearance of a report.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    Nominal Distribution( Column( :age ) ),
    Continuous Distribution( Column( :weight ) ),
    SendToReport( Dispatch( "age", "Distrib Nom Hist", FrameBox, {Frame Size( 178, 318 )} ) )
);

Sync to Data Table Changes

Syntax: obj << Sync to Data Table Changes

Description: Sync with the exclude and data changes that have been made.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
dist = Distribution( Continuous Distribution( Column( :POP ) ) );
Wait( 1 );
dt << Delete Rows( dt << Get Rows Where( :Region == "W" ) );
dist << Sync To Data Table Changes;

Title

Syntax: obj << Title( "new title" )

Description: Sets the title of the platform.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
obj << Title( "My Platform" );

Top Report

Syntax: obj << Top Report

Description: Returns a reference to the root node in the report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = dt << Time Series( Y( :steel shipments ) );
r = obj << Top Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

Transform Column

Syntax: obj = <Platform>(... Transform Column(<name>, Formula(<expression>), [Random Seed(<n>)], [Numeric|Character|Expression], [Continuous|Nominal|Ordinal|Unstructured Text], [column properties]) ...)

Description: Create a transform column in the local context of an object, usually a platform. The transform column is active only for the lifetime of the platform.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    Transform Column( "age^2", Format( "Fixed Dec", 5, 0 ), Formula( :age * :age ) ),
    Continuous Distribution( Column( :"age^2"n ) )
);

View Web XML

Syntax: obj << View Web XML

Description: Returns the XML code that is used to create the interactive HTML report.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Bivariate( Y( :Weight ), X( :Height ) );
xml = obj << View Web XML;

Window View

Syntax: obj = Time Series(...Window View( "Visible"|"Invisible"|"Private" )...)

Description: Set the type of the window to be created for the report. By default a Visible report window will be created. An Invisible window will not appear on screen, but is discoverable by functions such as Window(). A Private window responds to most window messages but is not discoverable and must be addressed through the report object

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( Window View( "Private" ), Y( :weight ), X( :height ), Fit Line );
eqn = Report( biv )["Linear Fit", Text Edit Box( 1 )] << Get Text;
biv << Close Window;
New Window( "Bivariate Equation",
    Outline Box( "Big Class Linear Fit", Text Box( eqn, <<Set Base Font( "Title" ) ) )
);

Damped-Trend Linear Exponential Smoothing

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Difference

Item Messages

Autocorrelation

Syntax: obj << Autocorrelation( state=0|1 )

Description: Displays or hides the Autocorrelation in the Difference report. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Autocorrelation( 1 ) );

Connecting Lines

Syntax: obj << Connecting Lines( state=0|1 )

Description: Displays or hides the lines connecting the points on the Difference Graph. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Connecting Lines( 1 ) );

Difference Graph

Syntax: obj << Difference Graph( state=0|1 )

Description: Displays or hides the Difference Graph. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Difference Graph( 1 ) );

Mean Line

Syntax: obj << Mean Line( state=0|1 )

Description: Displays or hides the mean line on the Difference Graph.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Mean Line( 1 ) );

Partial Autocorrelation

Syntax: obj << Partial Autocorrelation( state=0|1 )

Description: Displays or hides the Partial Autocorrelation in the Difference report. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Partial Autocorrelation( 1 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Save

Syntax: obj << Save

Description: Saves the Difference values in a new column in the data table.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Save );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Displays or hides the points on the Difference Graph. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Show Points( 1 ) );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram in the Difference report.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Difference( 1, 0, 0, Variogram( 1 ) );

Double (Brown) Exponential Smoothing

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Linear (Holt) Exponential Smoothing

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Seasonal ARIMA

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Seasonal Exponential Smoothing

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Simple Exponential Smoothing

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Simple Moving Average

Item Messages

Add Model

Syntax: obj << Add Model( Window Width, <Centered> )

Description: Add a simple moving average model. Model is identified by moving window width. The optional argument indicates whether the average is centered.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
sma = obj << Simple Moving Average( Add Model( 10 ) );
sma << Add Model( 15, Centered );

Connecting Lines

Syntax: obj << Connecting Lines( <1|0> )

Description: Graph option for displaying connected lines.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
sma = obj << Simple Moving Average( Connecting Lines );

Get Results

Syntax: obj << Get Results

Description: Return all simple moving average models as a JSL object.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
resultobj = obj << Simple Moving Average( Get Result );

Remove Model

Syntax: obj << Remove Model( Window Width, <Centered> )

Description: Remove a simple moving average model. Model is identified by moving window width.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
obj << Simple Moving Average( Remove Model( 5 ) );

Remove Report

Syntax: obj << Remove Report

JMP Version Added: 16

Save to Data Table

Syntax: obj << Save to Data Table

Description: Save all simple moving average models to a data table, and return the data table handle

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
resultdt = obj << Simple Moving Average( Save to Data Table );

Show Points

Syntax: obj << Show Points( <1|0> )

Description: Graph option for displaying points.

dt = Open( "$SAMPLE_DATA/Stock Prices.jmp" );
obj = Time Series( Y( :Close ), Simple Moving Average( Add Model( 5 ) ) );
sma = obj << Simple Moving Average( Show Points( 0 ) );

Transfer Function Model

Item Messages

Alternative Parameterization

Syntax: obj << Alternative Parameterization( state=0|1 )

Description: Specifies whether the general regression coefficient is factored out of the numerator polynomials.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Alternative Parameterization( 1 )
);

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Autocorrelations( 1 )
);
(obj << report)["Residuals"] << Close( 0 );

Compute Objective

Syntax: obj << Compute Objective

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Create SAS Job
);

Import New Inputs

Syntax: obj << Import New Inputs

JMP Version Added: 16

Maximum Iterations

Syntax: obj << Maximum Iterations( number )

Description: Specifies the maximum number of iterations.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Maximum Iterations( 10 )
);

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Removes the constraints on the AR and MA coefficients.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    No Constrain( 1 )
);

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the Intercept to zero.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    No Intercept( 1 )
);

Number of Forecast Periods

Syntax: obj << Number of Forecast Periods( number )

Description: Specifies the number of periods for forecasting.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Number of Forecast Periods( 10 )
);

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Partial Autocorrelations( 1 )
);
(obj << report)["Residuals"] << Close( 0 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Plot( 1 )
);
(obj << report)["Residuals"] << Close( 0 );

Prediction Interval

Syntax: obj << Prediction Interval( number )

Description: Sets the level of the confidence intervals displayed.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) )
);
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    :Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Confidence Intervals( 0.99 )
);

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Save Columns
);

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/SeriesJ.jmp" );
obj = Time Series( Y( :Output CO2 ), Input List( :Input Gas Rate ) );
obj << Transfer Function(
    Order( 2, 0, 0 ),
    Seasonal( 0, 0, 0, 0 ),
    Input Gas Rate( Order( 2, 0, 2 ), Seasonal( 0, 0, 0, 0 ), Lag( 3 ) ),
    Variogram( 1 )
);
(obj << report)["Residuals"] << Close( 0 );

Winters Method (Additive)

Item Messages

Actual

Syntax: obj << Actual( state=0|1 )

Description: Selects the Actual data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Actual( 1 ), Save Columns );

Autocorrelations

Syntax: obj << Autocorrelations( state=0|1 )

Description: Displays or hides the autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Confidence Intervals

Syntax: obj << Confidence Intervals( number )

Create SAS Job

Syntax: obj << Create SAS Job

Description: Creates a SAS Job to launch SAS and run the analysis in PROC ARIMA.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Create SAS Job;

Innovations

Syntax: obj << Innovations( state=0|1 )

Description: On by default.

JMP Version Added: 16

Lower Confidence Limit

Syntax: obj << Lower Confidence Limit( state=0|1 )

Description: Selects the Lower 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Lower Confidence Limit( 1 ), Save Columns );

No Constrain

Syntax: obj << No Constrain( state=0|1 )

Description: Lifts the constraint on the autoregressive parameters to always remain within the stable region and the moving average parameters within the invertible region when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Constrain( 1 ) );

No Intercept

Syntax: obj << No Intercept( state=0|1 )

Description: Sets the intercept to zero when launching an ARIMA model.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, No Intercept( 1 ) );

Partial Autocorrelations

Syntax: obj << Partial Autocorrelations( state=0|1 )

Description: Displays or hides the partial autocorrelations plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Partial Autocorrelations( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Plot

Syntax: obj << Plot( state=0|1 )

Description: Displays or hides the residual statistics plot. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Plot( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );

Predicted

Syntax: obj << Predicted( state=0|1 )

Description: Selects the Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Predicted( 1 ), Save Columns );

Prediction Interval

Syntax: obj << Prediction Interval( level )

Description: Sets the size of the confidence interval about the prediction for the ARIMA model. The default size is 0.95.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 1, 0, Forecasting Interval( 0.99 ) );

Remove Fit

Syntax: obj << Remove Fit

JMP Version Added: 16

Residuals

Syntax: obj << Residuals( state=0|1 )

Description: Selects the Residuals values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Residuals( 1 ), Save Columns );

Save Columns

Syntax: obj << Save Columns

Description: Creates a new data table containing the actual and predicted values together with standard errors, residuals and 95% prediction intervals about the response. This option is available for all ARIMA, Smoothing, and Transfer Function models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Columns;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the Prediction Formula to a new column in the data table. This option is available for all ARIMA and Smoothing models.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Arima( 1, 0, 0 );
obj2 << Save Prediction Formula;

Show Confidence Interval

Syntax: obj << Show Confidence Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Confidence Interval( 0 );

Show Points

Syntax: obj << Show Points( state=0|1 )

Description: Shows or hides points on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Show Points( 1 ) );

(obj << report)["Model Comparison"] << Close( 1 );

Show Prediction Interval

Syntax: obj << Show Prediction Interval( state=0|1 )

Description: Shows or hides prediction intervals on the Time Series Forecast Plot. This option is available for all ARIMA and Smoothing models. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj2 = obj << Simple Exponential Smoothing( Zero to One );
obj2 << Show Prediction Interval( 0 );

Std Error of Predicted

Syntax: obj << Std Error of Predicted( state=0|1 )

Description: Selects the Standard Error of Predicted values data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Std Error of Predicted( 1 ), Save Columns );

Time

Syntax: obj << Time( state=0|1 )

Description: Selects the Time data column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ), Time ID( :Date ) );
obj << Arima( 1, 0, 0, Time( 0 ), Save Columns );

Upper Confidence Limit

Syntax: obj << Upper Confidence Limit( state=0|1 )

Description: Selects the Upper 95% Confidence Limit values column for saving with the Save Columns command. On by default.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series( Y( :Steel Shipments ) );
obj << Arima( 1, 0, 0, Upper Confidence Limit( 1 ), Save Columns );

Variogram

Syntax: obj << Variogram( state=0|1 )

Description: Displays or hides the Variogram.

dt = Open( "$SAMPLE_DATA/Time Series/Steel Shipments.jmp" );
obj = Time Series(
    Y( :Steel Shipments ),
    Winters Method(
        12,
        Custom( Level( Bounded( 0, 1 ) ), Trend( Bounded( 0, 1 ) ) ),
        Variogram( 1 )
    )
);
(obj << report)["Residuals"] << Close( 0 );
(obj << report)["Model Comparison"] << Close( 1 );