Hi r users,
I am trying to compute the "moving variance" of a large matrix. I now use a
loop but I am looking for a faster solution. Here is a sample of the code.
Source= matrix(rnorm(400),ncol=100)
variances= matrix(rep(NA,4*100),ncol=100)
for (i in 1:80) {variances[,i]=apply(Source[,i:(i+80)],1,var)}
any idea? Many thanks in advance.
Vincent.
--
View this message in context: http://r.789695.n4.nabble.com/Saving-run-time-in-loop-tp3462228p3462228.html
Sent from the R help mailing list archive at Nabble.com.
Saving run time in loop
3 messages · vincent.deluard, Rolf Turner, Dennis Murphy
On 20/04/11 18:30, vincent.deluard wrote:
Hi r users,
I am trying to compute the "moving variance" of a large matrix. I now use a
loop but I am looking for a faster solution. Here is a sample of the code.
Source= matrix(rnorm(400),ncol=100)
variances= matrix(rep(NA,4*100),ncol=100)
for (i in 1:80) {variances[,i]=apply(Source[,i:(i+80)],1,var)}
any idea? Many thanks in advance.
It's not at all clear what you are actually trying to do, and the sample
code that you give does not work. I.e. it throws an error.
Be more careful and think more clearly.
cheers,
Rolf Turner
Hi: Perhaps rollapply() in the zoo package might be helpful. Dennis On Tue, Apr 19, 2011 at 11:30 PM, vincent.deluard
<vincent.deluard at trimtabs.com> wrote:
Hi r users,
I am trying to compute the "moving variance" of a large matrix. I now use a
loop but I am looking for a faster solution. Here is a sample of the code.
Source= matrix(rnorm(400),ncol=100)
variances= matrix(rep(NA,4*100),ncol=100)
for (i in 1:80) {variances[,i]=apply(Source[,i:(i+80)],1,var)}
any idea? Many thanks in advance.
Vincent.
--
View this message in context: http://r.789695.n4.nabble.com/Saving-run-time-in-loop-tp3462228p3462228.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________ R-help at 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.