From: ted.dunning@gmail.com   
      
   On Jul 14, 9:29 pm, Francois  wrote:   
   > I am looking for a regression model that can predict multiple   
   > variables at the same time, i.e. multiple dependent variables.   
      
   Take a look at latent variable models.   
      
   Also, can't this problem just be decomposed into a conventional   
   regression on a single dependent variable?  For a linear problem, you   
   seem to be wanting to find a minimum error solution of this system:   
      
   A_1 x = b_1   
   A_2 x = b_2   
   ...   
   A_n x = b_n   
      
   This could be stacked into a single system using:   
      
   [A_1 ; A_2 ; ... ; A_n] x = [b_1; b_2; ... ; b_n]   
      
   (where ; indicates vertical stacking as in matlab or octave).   
      
   Other kinds of regression typically involve a link function of some   
   kind and possibly multiple levels of linear combination and linking.   
   Regardless of that, this stacking trick should still work just fine.   
      
   So doesn't this mean that very ordinary techniques will work?   
      
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