How to save predicted values into matrix or list without saving into existing data table

[#1]

Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = Bivariate( Y( :Weight ), X( :Height ) )<<Group by(:sex);;
obj<<Fit spline(0.1, Standardized,{Save Predicteds});

tried lis below , it won't work.

val_predict_ls=obj<<Save Predicteds. 

[#2 · Accepted solution]

I am not sure how to create the matrix without creating the column in the data table, but here is a method that functionally will do what you want

Names Default To Here( 1 );

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

// Get the groupings for the sex column
Summarize( dt, bysex = by( :sex ) );
obj = Bivariate( Y( :Weight ), X( :Height ) ) << Group by( :sex );
obj << Fit spline( 0.1, Standardized, {Save Predicteds} );

// Create the matricies for the groups and delete the
// columns from the data table
For( i = N Items( bysex ), i >= 1, i--,
	Eval(
		Parse(
			bysex[i] ||
			"_Predicted_Matrix = column(dt,N Col(dt))<<get values;"
		)
	);
	dt << delete columns( N Cols( dt ) );
);
Show( f_Predicted_Matrix, m_Predicted_Matrix );

[#3]

Thanks.
My attempt was trying get the a few key summary values like mean, sigma etc from a group of predicted values based on a large data base.
Looks like, need to go your way by saving into data table, then deleted them.