Or better:
tapply(x0, y0, mean)
On Mon, May 3, 2010 at 2:35 PM, Henrique Dallazuanna wrote:
> Try this:
>
> rowsum(x0, y0)[,1]/table(y0)
>
>
> On Mon, May 3, 2010 at 2:11 PM, song song wrote:
>
>> x0=rnorm(100)
>> y0=rpois(100,3)+1
>>
>> ind=as.data.frame(table(y0))
>>
>> ind1=ind[,1]
>> ind2=i
I believe you are trying to find the mean of x0 for each level (group) of y0.
try this:
by(x0, y0, mean)
or if you want a vector (e.g., to merge into a matrix)
c(by(x0, y0, mean))
Best regards,
Josh
On Mon, May 3, 2010 at 10:11 AM, song song wrote:
> x0=rnorm(100)
> y0=rpois(100,3)+1
>
> in
Try this:
rowsum(x0, y0)[,1]/table(y0)
On Mon, May 3, 2010 at 2:11 PM, song song wrote:
> x0=rnorm(100)
> y0=rpois(100,3)+1
>
> ind=as.data.frame(table(y0))
>
> ind1=ind[,1]
> ind2=ind[,2]
>
> phi=NULL
> for (i in 1:length(ind2)){
> phi[i]=sum(x0[y0==ind1[i]])/ind2[i]
> }
>
>[[alterna
as.vector(do.call(c, lapply(split(x0, y0), mean)))
Test with data generated according to your code:
> phi=NULL
> for (i in 1:length(ind2)){
+ phi[i]=sum(x0[y0==ind1[i]])/ind2[i]
+ }
> phi
[1] -0.18922774 0.36333115 -0.04295032 -0.13892563 -0.03968301 0.33326034
[7] 0.28649576 -0.03786830
> a
x0=rnorm(100)
y0=rpois(100,3)+1
ind=as.data.frame(table(y0))
ind1=ind[,1]
ind2=ind[,2]
phi=NULL
for (i in 1:length(ind2)){
phi[i]=sum(x0[y0==ind1[i]])/ind2[i]
}
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