Robust Fit Outliers - different row set selected and excluded as outliers

[#1]

Dear community,

I have a stacked data table, and want to exclude outliers by a Label (e.g. an element for some measurements).

In the robust fit outlier platform I can detect outliers and than can select or exclude corresponding rows.

For my understanding, rows that are selected than or excluded, should be exactly the same ones.

And that is the case for the below sample data table used in the JSL below.

// from scripting index

Names Default To Here( 1 );

dt = Open( "$SAMPLE_DATA/Water Treatment.jmp" );

// similar, but stacked data and usage of by role

dt_stack = dt << Stack(
	columns( Column Group( "Sensor Measurements" ) ),
	Source Label Column( "Label" ),
	Stacked Data Column( "Data" ),
	Output Table( "Water Treatment stacked.jmp" )
);

obj_select = dt_stack << Explore Outliers( Y( :Data ), By( :Label ), Robust fit outliers, select rows() );
obj_exclude = dt_stack << Explore Outliers( Y( :Data ), By( :Label ), Robust fit outliers, exclude rows() );
Show( N Items( dt_stack << get selected rows() ), N Items( dt_stack << get excluded rows() ) );

But in my case with real data, I get different rows selected and excluded, it looks to me that the platform works well in identifying the outliers, but the exclude operation fails to exclude one row (that has been selected as outlier).

Any idea on this behaviour?