Gaussian Process

Associated Constructors

Gaussian Process

Syntax: Gaussian Process( Y( column ), X( columns ) )

Description: Models the relationship between a continuous response and one or more continuous predictors as a spline with interpolation.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );

Columns

By

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

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), By( _bycol ) );

X

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

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );

Y

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

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );

Item Messages

Block Size

Syntax: obj << Block Size( number )

Description: Sets the number of observations to place in each block for Fast GASP.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), Fast GASP( 1 ), Block Size( 32 ) );

Contour Profiler

Syntax: obj << Contour Profiler( state=0|1 )

Description: Shows or hides the Contour Profiler.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Contour Profiler( 1 );

Estimate Nugget

Syntax: obj << Estimate Nugget( state=0|1 )

Description: Introduces a ridge parameter into the estimation procedure. This smooths over the noise instead of perfectly interpolating.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), Estimate Nugget( 1 ) );

Fast GASP

Syntax: obj << Fast GASP( state=0|1 )

Description: The Fast GASP option allows for fitting models with thousands of rows.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), Fast GASP( 1 ) );

Profiler

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

Description: Shows or hides the Prediction Profiler.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Profiler( 1 );

Publish Prediction Formula

Syntax: obj << Publish Prediction Formula

Description: Builds the prediction formula and publishes it as a formula column script in Formula Depot.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Publish Prediction Formula;

Publish Variance Formula

Syntax: obj << Publish Variance Formula

Description: Builds the variance formula and publishes it as a formula column script in Formula Depot.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Publish Variance Formula;

Save Jackknife Predicted Values

Syntax: obj << Save Jackknife Predicted Values

Description: Saves the jackknife predicted values to a new column in the data table.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Save Jackknife Predicted Values;

Save Prediction Formula

Syntax: obj << Save Prediction Formula

Description: Saves the prediction formula to a new column in the data table.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Save Prediction Formula;

Save Variance Formula

Syntax: obj << Save Variance Formula

Description: Saves the variance formula to a new column in the data table.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Save Variance Formula;

Set Correlation Function

Syntax: obj << Set Correlation Function( structure=Gaussian )

Description: Sets the correlation structure used in the model.

Gaussian restricts the correlation between two responses to be nonzero.

Cubic allows the correlations to be zero for points far enough apart. "Gaussian" by default.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process(
    Y( :Y ),
    X( :X1, :X2 ),
    Set Correlation Function( "Gaussian" )
);

Set Minimum Theta

Syntax: obj << Set Minimum Theta( number )

Description: Sets the minimum theta value used in the fitted model.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), Set Minimum Theta( 0.5 ) );

Set Nugget

Syntax: obj << Set Nugget( number )

Description: Sets the size of the nugget as a constant used as a ridge parameter into the estimation procedure.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), Set Nugget( 0.2 ) );

Surface Profiler

Syntax: obj << Surface Profiler( state=0|1 )

Description: Shows or hides the Surface Profiler.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
obj << Surface Profiler( 1 );

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" ) );

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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
t = obj << Get Script With Data Table;
Show( t );

Get Timing

Syntax: obj << Get Timing

Description: Times the platform launch.

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), By( _bycol ) );
obj[1] << Save Script for All Objects To Data Table;

Example 2

dt = Open( "$SAMPLE_DATA/2D Gaussian Process Example.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ), 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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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/2D Gaussian Process Example.jmp" );
obj = dt << Gaussian Process( Y( :Y ), X( :X1, :X2 ) );
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 = Gaussian Process(...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" ) ) )
);