On Wed, 8 Mar 2006, ronggui wrote:
Thank you for all .
One more question.How can I calculate these efficiently?
set.seed(100)
dat<-data.frame(x1=rnorm(20),x2=rnorm(20),u=rnorm(20),id=round(2*runif(20)))
# In this example,id's elements are 0,1,2.
y<-list()
for (i in 0:2){
X<-as.matrix(subset(dat,id==i,c("x1","x2")))
u<-as.matrix(subset(dat,id==i,c("u")))
y[[i+1]]<-t(X)%*%u%*%t(u)%*%X
}
y[[1]]+y[[2]]+y[[3]]
People have already told you about crossprod, so crossprod(crossprod(X,u))
would seem an obvious improvement over the matrix multiplications.
There is a better solution, though.
Xu<-dat[,c("x1","x2")]*dat[,"u"]
crossprod( rowsum(Xu, dat$id))
-thomas
the above code is not elegant.And my second solution to this problem
is using by to get a list.
matlis<-by(dat, dat$id, function(x){
a<-as.matrix(x[,c("x1","x2")])
b<-as.matrix(x[, "u"])
t(a) %*% b %*% t(b) %*% a
})
S <- matrix(unlist(matlis), 4, length(matlis))
S1 <- matrix(rowSums(S), 2, 2)
The code works ,but I want to ask if there is any other more better
ways to do it? It seems that this kind of computation is quite common.
2006/2/28, Gabor Grothendieck <[EMAIL PROTECTED]>:
Try:
crossprod(x)
or
t(x) %*% x
On 2/28/06, ronggui <[EMAIL PROTECTED]> wrote:
This is the code:
x<-matrix(rnorm(20),5)
y<-list()
for (i in seq(nrow(x))) y[[i]]<-t(x[i,,drop=F])%*%x[i,,drop=F]
y[[1]]+y[[2]]+y[[3]]+y[[4]]+y[[5]]
How can I do it without using for loops?
Thank you in advance!
--
ronggui
Deparment of Sociology
Fudan University
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--
??????
Deparment of Sociology
Fudan University
Thomas Lumley Assoc. Professor, Biostatistics
[EMAIL PROTECTED] University of Washington, Seattle
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