Hello,..
Apologies for the newbie question but...
I have a matrix R, and I know that *B %*% t(b) = R*
*I'm trying to solve for B *(aka. 'factoring the correlation matrix' I
think)
Please help!
I've read that 'to solve for B we define the eigenvalues of R and then
apply the techniques of Principal Component Analysis'
This made me reach for princomp() but now I'm stuck.
I think to understand, that I should be doing this:
pc<-princomp(covmat=R, cor=TRUE)
This gives me :
Standard deviations:
Comp.1 Comp.2 Comp.3
1.208492 1.076105 0.617694
But what do I do with that, in order to construct B ??
Thanks for any help anyone can give,... even if it's just a pointer to
an example... free beer to anyone who can save me.
/Shawn
p.s. I read/understand Thursstone_1944 which gives a graphical method of
Factoring the Correlation Matrix, which I understand... but surely R
provides me a way of determining B? And I know that the answer is
encrypted in Harman_1960.
p.p.s. Here's my R (in case you're curious and want to help):
R<-matrix(c(0.6099, 0.2558, 0.1858,
0.2558, 0.5127, -.1384,
0.1858, -0.1384, 0.9351 ),
nrow=3, ncol=3, byrow=TRUE)
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