On Sep 15, 2011, at 5:57 PM, D_Tomas wrote:
Hi there,
I need to do the same thing as cumsum but with the variance and
skewness. I
have tried to do a loop for like this:
var.value <- vector(mode = "numeric", length = length(daily))
for (i in (1:length(daily))) {
var.value[i] <- var(daily[1:i])
}
daily <- rnorm(1000000)
mbar <- mean(daily)
cumvar <- cumsum( (daily-cumsum(daily)/1:length(daily) )^2)
cumskew <- cumsum( (daily-cumsum(daily)/1:length(daily))^3)/
cumvar^(3/2)
Hmm. Not sure it should be defined at the first couple of indices.
First version scrapped but this one seems to be working:
> str(cumvar)
num [1:1000000] 0 0.265 0.334 1.324 1.845 ...
> str(cumskew)
num [1:1000000] NaN -1 -0.8 0.546 0.182 ...
> plot(cumskew[1:1000]) # settles out as it should for
> plot(cumvar[1:1000]) # appears to be linear with index
But because my dataset is so huge, I run out of memory.....
Clean up your workspace and don't run lots of apps in teh background.
That operation should not have been memory intensive. It would have
been slow if you had not preallocated var.value, though.
Any ideas?!?!
Much appreciate it!
--
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