[R] Matrix oriented computing

[Patrick Burns]

I believe that the following is what you want:

x <- c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995)
dof <- 1:100
ans <- outer(x, dof, qchisq)
dimnames(ans) <- list(x, dof)


Note that 'df' is not a very auspicious name for an object since
it is the name of a function. 

Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")

Sigbert Klinke wrote:

>Hi,
>
>I want to compute the quantiles of Chi^2 distributions with different 
>degrees of freedom like
>
>x<-cbind(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995)
>df<-rbind(1:100)
>m<-qchisq(x,df)
>
>and hoped to get back  a  length(df) times length(x)  matrix with the 
>quantiles. Since this does not work, I use
>
>x<-c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995)
>df<-c(1:100)
>m<-qchisq(x,df[1])
>for (i in 2:length(df)) {
>  m<-rbind(m,qchisq(x,df[i]))
>}
>dim(m)<-c(length(df),length(x))
>
>Is there a way to avoid the for loop ?
>
>Thanks Sigbert
>
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