Hi,
On Aug 17, 2009, at 5:09 PM, Pavlo Kononenko wrote:
Hi, everyone,
This is a little silly, but I cant figure out the algorithm behind
lm.fit function used in the context of promax rotation algorithm:
The promax function is:
promax <- function(x, m = 4)
{
if(ncol(x) < 2) return(x)
dn <- dimnames(x)
xx <- varimax(x)
x <- xx$loadings
Q <- x * abs(x)^(m-1)
U <- lm.fit(x, Q)$coefficients
d <- diag(solve(t(U) %*% U))
U <- U %*% diag(sqrt(d))
dimnames(U) <- NULL
z <- x %*% U
U <- xx$rotmat %*% U
dimnames(z) <- dn
class(z) <- "loadings"
list(loadings = z, rotmat = U, crap = x, coeff = Q)
}
And the line I'm having trouble with is:
U <- lm.fit(x, Q)$coefficients
Isn't this doing a least squares regression using the predictor
variables in x and the (I guess) real valued numbers in vector Q?
x is a matrix of n (observations) by p (predictors)
The $coefficients is just taking the vector of coefficients/weights
over the predictors -- this would be a vector of length p -- such that
x %*% t(t(U)) ~ Q
* t(t(U)) is ugly, but I just want to say get U to be a column vector
* ~ is used as "almost equals")
You'll need some numerical/scientific/matrix library in java, perhaps
this could be a place to start:
http://commons.apache.org/math/userguide/stat.html#a1.5_Multiple_linear_regression
Hope that helps,
-steve
--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
