For some work I'm doing, I need to apply PCA to data containing missing values. So I dug up some old code that I had around, which implements Stock and Watson's EM algorithm (detailed in the 2002 JBES article).
I'm attaching a script with the function and an example if anyone's interested.
Of course, it'd be nice to make this procedure more readily available to gretl users. I see four (not mutually exclusive) ways of doing so:
1) modify our existing "pca" command to handle missing values; 2) modify our existing "princomp" function to handle missing values; 3) create a small self-contained function package; 4) integrate the code into the existing "staticfactor" function package. Which one do you this is best? ------------------------------------------------------- Riccardo (Jack) Lucchetti Dipartimento di Scienze Economiche e Sociali (DiSES) Università Politecnica delle Marche (formerly known as Università di Ancona) r.lucche...@univpm.it http://www2.econ.univpm.it/servizi/hpp/lucchetti -------------------------------------------------------
pca_with_nas.inp
Description: application/gretlscript
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