Principal Components

Associated Constructors

Principal Components

Syntax: Principal Components( Y( columns ) )

Description: Models the variation in a set of variables in terms of a smaller number of independent linear combinations (principal components) of those variables.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane )
);

Columns

By

Syntax: obj = Principal Components(...<By( column(s) )>...)

Description: Performs a separate analysis for each level of the specified column.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    By( _bycol )
);

Freq

Syntax: obj = Principal Components(...<Freq( column )>...)

Description: Specifies a column whose values assign a frequency to each row for the analysis.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
dt << New Column( "_freqcol", Numeric, Continuous, Formula( Random Integer( 1, 5 ) ) );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Freq( _freqcol )
);

Supplementary Variable

Syntax: obj << Supplementary Variable( column(s) )

Description: Specifies one or more supplementary variables. Supplementary variables are not used in any of the calculations in the platform and including them does not affect the results. These variables can improve data interpretation or be used in future analyses.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Z( :Species ),
    Standardize( "Standardized" )
);

Weight

Syntax: obj = Principal Components(...<Weight( column )>...)

Description: Specifies a column whose values assign a weight to each row for the analysis.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
dt << New Column( "_weightcol", Numeric, Continuous, Formula( Random Beta( 1, 1 ) ) );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Weight( _weightcol )
);

Y

Syntax: obj = Principal Components(...<Y( column(s) )>...)

Description: Specifies the variables to analyze for components.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane )
);

Z

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

Description: Specifies one or more supplementary variables. Supplementary variables are not used in any of the calculations in the platform and including them does not affect the results. These variables can improve data interpretation or be used in future analyses.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Z( :Species ),
    Standardize( "Standardized" )
);

Item Messages

3D Score Plot

Syntax: obj << 3D Score Plot( state=0|1 )

Description: Shows or hides a 3-D scatterplot of the principal components as rays in a three-dimensional space.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << "3D Score Plot"n( 1 );

Arrow Lines

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

Description: Shows or hides the arrow lines in the graph.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Arrow Lines( 0 );

Bartlett Test

Syntax: obj << Bartlett Test( state=0|1 )

Description: Shows or hides a report of the results of the homogeneity test for each of the principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Bartlett Test( 1 );

Biplot

Syntax: obj << Biplot( number )

Description: Shows or hides a plot that overlays the score plot and the loading plot for the specified number of components.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Biplot( 2 );

Cluster Components

Syntax: obj << Cluster Components( state=0|1 )

Description: Shows or hides the Standardized Components report, which contains the eigenvectors of the first principal component within each cluster. On by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Cluster Components( 1 ) );

Cluster Members

Syntax: obj << Cluster Members( state=0|1 )

Description: Shows or hides a report of the variables in each cluster. On by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Cluster Members( 1 ) );

Cluster Summary

Syntax: obj << Cluster Summary( state=0|1 )

Description: Shows or hides a report that summarizes the results of variable clustering. On by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Cluster Summary( 1 ) );

Cluster Variables

Syntax: obj << Cluster Variables( state=0|1 )

Description: Clusters variables into similar groups.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Cluster Variables( 1 );

Color Map on Correlations

Syntax: obj << Color Map on Correlations( state=0|1 )

Description: Shows or hides a color map of the correlations between variables, where the variables are arranged so that members of the same cluster are adjacent in the plot. On by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Color Map On Correlations( 1 ) );

Coordinate Matrix

Syntax: obj << Coordinate Matrix( state=0|1 )

Description: Shows or hides a table that contains the component coordinates. This option is available only when there is a categorical variable in the analysis.

JMP Version Added: 19

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width, :Species ),
    Standardize( "Standardized" )
);
obj << Coordinate  Matrix( 1 );

Correlations

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

Description: Shows or hides a matrix of correlation coefficients that summarize the strength of the linear relationships between each pair of Y variables.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Correlations( 1 );

Covariance Matrix

Syntax: obj << Covariance Matrix( state=0|1 )

Description: Shows or hides a matrix of covariances for each pair of Y variables.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Covariance Matrix( 1 );

Eigenvalues

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

Description: Shows or hides the sorted eigenvalues, their percent of variation, and the cumulative percent of variation.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Eigenvalues( 1 );

Eigenvectors

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

Description: Shows or hides a report of the eigenvectors for each of the principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Eigenvectors( 1 );

Estimation Method

Syntax: Estimation Method( REML | ML | Robust | Row-wise | Pairwise | Full SVD | Truncated SVD | Randomized SVD | Robust SVD | Sparse SVD)

Description: Sets the estimation method for computing the correlations.

If there are no missing values, then the default is Row-wise.

If there are missing values, and the number of variables <= 10 and the number of rows <=5000, then the default is REML.

If there are missing values, and the number of variables > 10 or number of rows > 5000, then the default is Pairwise. "Default" by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" ),
    Estimation Method( "REML" )
);

Factor Analysis

Syntax: obj << Factor Analysis( ML|PC, ONE|SMC, n Rotated, Varimax| Biquartimax| Equamax| Factorparsimax| Orthomax| Parsimax| Quartimax| Biquartimin| Covarimin| Obbiquartimax| Obequamax| Obfactorparsimax| Obequamax| Obfactorparsimax| Oblimin| Obparsimax| Obquartimax| Obvarimax| Quartimin| UnRotated| Promax )

Description: Shows or hides a report of the factor rotation pattern for the principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Factor Analysis( "ML", "SMC", 2, "Varimax" );

Formatted Loading Matrix

Syntax: obj << Formatted Loading Matrix( state=0|1 )

Description: Shows or hides a report that contains the formatted component loadings.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Formatted Loading Matrix( 1 );

Impute Missing Data

Syntax: obj << Impute Missing Data

Description: Imputes missing values for all the Y variables and creates a new data table containing both the existing values and newly imputed missing data values.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ) );
obj << Impute Missing Data( 1 );

Launch Fit Model

Syntax: obj << Launch Fit Model

Description: Launches Fit Model with the Most Representative variables as predictors. Select Save Cluster Components first if you want to use these as predictors.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Launch Fit Model );

Loading Matrix

Syntax: obj << Loading Matrix( number )

Description: Show or hides a table that contains the component loadings.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Loading Matrix( 1 );

Loading Plot

Syntax: obj << Loading Plot( number )

Description: Shows or hides a matrix of plots that are two-dimensional representations of factor loadings.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Loading Plot( 2 );

Missing value imputation

Syntax: obj = Principal Components(...Missing value imputation( state=0|1 )...)

Description: Imputes missing values through matrix completion. This option is applicable to wide methods. On by default.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10, :Lead ),
    Estimation Method( "Truncated SVD" ),
    Number of Components( 6 ),
    Missing value imputation( 0 ),
    Standardize( "Standardized" )
);

Model Driven Multivariate Control Chart

Syntax: obj << Model Driven Multivariate Control Chart

Description: Launches Model Driven Multivariate Control Chart for specified number of Components

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Model Driven Multivariate Control Chart( 2 );

Number of Components

Syntax: obj = Principal Components(...Number of Components( number=10 )...)

Description: Sets the number of components to be extracted. To reduce computation time, enter a small number of components. "10" by default.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Estimation Method( "Sparse" ),
    Number of Components( 3 ),
    Standardize( "Standardized" )
);

Outlier Analysis

Syntax: obj << Outlier Analysis( state=0|1 )

Description: Shows or hides the Outlier Analysis report, which enables you to detect outliers in the data through T² and contribution statistics.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Estimation Method( "Default" ),
    Standardize( "Standardized" ),
    Outlier Analysis( 1 )
);

Partial Contribution of Variables

Syntax: obj << Partial Contribution of Variables( number )

Description: Shows or hides a table that contains the partial contributions of variables and a plot of the partial contributions for the first three principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Partial Contribution of Variables(
    Plot of Partial Contribution of Variables( Overview( 3 ), "Side by side" )
);

Profiler for Predicteds

Syntax: obj << Profiler for Predicteds

Description: Launches a profiler for the predictions using the specified number of components.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Profiler for Predicteds( 2 );

Publish Components Formulas

Syntax: obj << Publish Components Formulas( number )

Description: Creates a specified number of principal component formulas and saves them as formula column scripts in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Estimation Method( "Wide" )
);
obj << Publish Components Formulas( 3 );

Publish Normalized DModX Formula

Syntax: obj << Publish Normalized DModX Formula( number )

Description: Saves the normalized DModX formula based on a specified number of principal components as a formula column script in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Publish Normalized DModX Formula( 3 );

Save Cluster Components

Syntax: obj << Save Cluster Components

Description: Saves the cluster (first principal) component for each cluster to the data table.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Correlations" );
obj << Cluster Variables( Save Cluster Components );

Save Imputed Formula

Syntax: obj << Save Imputed Formula

Description: Imputes values where the Y column values are missing. Creates and saves a new column with an imputation formula to the original data table.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ) );
obj << Save Imputed Formula( 1 );

Save Individual Partial Contributions

Syntax: obj << Save Individual Partial Contributions( number )

Description: Saves individual partial contributions to new columns in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Covariances" );
obj << Save Individual Partial Contributions( 3 );

Save Individual Squared Cosines

Syntax: obj << Save Individual Squared Cosines( number )

Description: Saves individual squared cosines to new columns in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Covariances" );
obj << Save Individual Squared Cosines( 3 );

Save Low Rank Principal Components

Syntax: obj << Save Low Rank Principal Components( number )

Description: Saves the principal component scores from the low-rank data, cleaned of outliers and noise. This option applies only to the Robust PCA estimation method.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" ),
    Estimation Method( "Robust PCA" ),
    Number of Components( 3 )
);
obj << Save Low Rank Principal Components( 3 );

Save Normalized DModX

Syntax: obj << Save Normalized DModX( number )

Description: Saves the normalized DModX values to a new column in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Covariances" );
obj << Save Normalized DMODX( 3 );

Save Predicteds

Syntax: obj << Save Predicteds( number )

Description: Saves the predicted variables with a specified number of principal components to new columns in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components( Y( :OZONE, :CO, :SO2, :NO, :PM10 ), "on Covariances" );
obj << Save Predicteds( 3 );

Save Predicteds as Component Formulas

Syntax: obj << Save Predicteds as Component Formulas

Description: Saves the component formulas for a specified number of principal components to new columns in the data table.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Save Predicteds As Component Formulas( 3 );

Save Principal Component Script

Syntax: obj << Save Principal Component Script( number )

Description: Saves a script to the script window that when run will create new columns in the data table for the given number of principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << save principal Component script( 3 );

Save Principal Component Values

Syntax: obj << Save Principal Component Values( number )

Description: Saves the given number of principal components to new non-formula columns in the data table, including from imputed cells.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Save Principal Component Values( 3 );

Save Principal Components

Syntax: obj << Save Principal Components( number )

Description: Saves the given number of principal components to new formula columns in the data table.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Save Principal Components( 3 );

Save Principal Components with Imputation

Syntax: obj << Save Principal Components with Imputation( number )

Description: Saves the given number of principal components computed using imputation on missing values to new columns in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Save Principal Components with Imputation( 3 );

Save Rotated Components

Syntax: obj << Save Rotated Components

Description: Saves the rotated components to new columns in the data table.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" ),
    Factor Analysis( "SMC", 2, "Varimax" )
);
obj << Save Rotated Components;

Save Rotated Components with Imputation

Syntax: obj << Save Rotated Components with Imputation

Description: Saves the rotated components computed using imputation on missing values to new columns in the data table. Note: This option is only available after the Factor Rotation has been run.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" ),
    Factor Analysis( "SMC", 2, "Varimax" )
);
obj << Save Rotated Components with Imputation;

Scatterplot Matrix

Syntax: obj << Scatterplot Matrix( number )

Description: Shows or hides a matrix of score and loading plots for a specified number of principal components.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Scatterplot Matrix( 4 );

Score Ellipse Coverage

Syntax: obj << Score Ellipse Coverage( "0.90"|"0.95"|"0.99"|"1-sigma"|"2-sigma"|"3-sigma"|"Other…" )

Description: Changes the alpha level for the confidence ellipses on the score plot for each pair of principal components.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Score Ellipse Coverage( 0.9 );

Score Ellipses

Syntax: obj << Score Ellipses( state=0|1 )

Description: Shows or hides confidence ellipses on the score plot for each pair of principal components.

JMP Version Added: 15

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Score Ellipses( 1 );

Score Plot

Syntax: obj << Score Plot( number )

Description: Shows or hides a matrix of scatterplots that contain the scores for each pair of the specified number of principal components.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Score Plot( 2 );

Score Plot with Imputation

Syntax: obj << Score Plot with Imputation( number of principal components )

Description: Shows or hides a matrix of scatterplots that contain the scores for each pair of the specified number of principal components, using imputation for missing values.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Score Plot with Imputation( 2 );

Scree Plot

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

Description: Shows or hides a line plot of the eigenvalues for each component.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Scree Plot( 1 );

Select component

Syntax: obj << Select component( <specify dimension to plot> )

Description: Selects the dimensions that are used as axes in the summary plots.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Standardize( "Standardized" )
);
obj << Select Component( 1, 3 );

Show Supplementary Variable

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

Description: Shows or hides the arrow lines for supplementary variables in the graph.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Z( :Species ),
    Standardize( "Standardized" )
);
obj << Show Supplementary Variable( 0 );

Squared Cosines of Variables

Syntax: obj << Squared Cosines of Variables( number )

Description: Shows or hides a table that contains the squared cosines of variables.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
obj = dt << Principal Components(
    Y( :OZONE, :CO, :SO2, :NO, :PM10 ),
    Standardize( "Standardized" )
);
obj << Squared Cosines of Variables(
    Plot of Squared Cosines of Variables( Overview( 3 ), "Stacked", "Horizontal" )
);

Standardize

Syntax: obj = Principal Components(...Standardize( "Standardized"|"Unscaled"|"Unscaled and Uncentered" )...)

Description: Specifies whether each column should be standardized individually.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Principal Components(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Estimation Method( "Row-wise" ),
    Standardize( "Standardized" )
);

Summary Plots

Syntax: obj << Summary Plots( state=0|1 )

Description: Shows or hides an outline node that contains a plot of the eigenvalues, a score plot, and a loading plot. On by default.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);
obj << Summary Plots( 1 );

on Correlations

Syntax: Principal Components( Y( columns ), On Correlations )

Description: Creates a principal components report using the correlation matrix.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    Standardize( "Standardized" )
);

on Covariances

Syntax: Principal Components( Y( columns ), On Covariances )

Description: Creates a principal components report using the covariance matrix.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    "on Covariances"
);

on Unscaled

Syntax: Principal Components( Y( column ), On Unscaled )

Description: Creates a principal components report using the unscaled data.

dt = Open( "$SAMPLE_DATA/Solubility.jmp" );
obj = dt << Principal Components(
    Y( :Ether, :Chloroform, :Benzene, :Carbon Tetrachloride, :Hexane ),
    "on Unscaled"
);