Re: Help on Partial Least Squares Algorithm

mike-nospam_at_darrettenterprises.com
Date: 03/16/05 

Date: 16 Mar 2005 10:36:24 -0800

mdtorre@freemail.it wrote:
> The PLS algorithm (on one target variable) does regression on some
> specific subsapace
> The regression problem is:
> y = XWQ + e
> where y is a single variable target vector nx1,
> X is a data vector nxP
> W is a subspace of X of pxk dimension (with k<p)
> Q are the kx1 regression coefficents.
> T=XW is the score plot.
>
> I need the W matrix of PLS only for visualization purpose, i.e. I
have
> to plot the score like a PCA.
> How can I calculate directly the subspace W? I don't want to use the
> more complex PLS algorithms (NIPALS or SIMPLS) that suppose that I
have
> more than one target variables and give me the regression coefficent
> matrix Q I don't need.
>
> In short: what is the formula to calculate W from X and y? (i.e.: fr
> PCA the W space is the k-biggest eigenvalue corresponding eigenvector
> space of X'*X given X standardized)
>
> Thank you very much
> Matteo

Maybe the folks on sci.math could help you. Cross-posting now...

Mike Darrett
http://www.darrettenterprises.com

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