Hi all,

I'm currently comparing more closely the different ways of how to compute principal components, leading to some remarks or suggestions (and questions) about the respective documentation.

1) eigensym:

(i) The resulting eigenvalues are ascending, and there's a relatively complicated code example about how to get them in descending order, namely: 

I guess that this help predates the introduction of the mreverse() function? 

So, OK to change the help example there? Or am I missing something? 

Let's change it, yes. Could you please see to it?

2) princomp:

There's a verbal explanation of how they are computed, which I find difficult to follow. 

Yes, that occurred to me too. I think we may want to reword it a little.

I have verified that the following computations coincide:  [...]

That's not necessarily true, because the eigenvectors (and hence the principal components) are identified up to a sign switch. Moreover, there's an even neater way:

<hansl>
clear
A = mnormal(30,10)

# SVD-based
matrix ps = empty 
l = svd(cdemean(A), &ps)
ps = ps .* l
</hansl>

I think it would be helpful to include an example like this one in the princomp help. Or maybe a variant based on the correlation matrix (default in princomp) instead of the covariance like here. OK?

Fine by me.

-------------------------------------------------------
  Riccardo (Jack) Lucchetti
  Dipartimento di Scienze Economiche e Sociali (DiSES)

  Università Politecnica delle Marche
  (formerly known as Università di Ancona)

  r.lucchetti@univpm.it
  http://www2.econ.univpm.it/servizi/hpp/lucchetti
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