[R] Speed up studentized confidence intervals ?

[David Winsemius]

I’m wondering if this is an X-Y problem. (A request to do X when the real problem should be doing Y. ) You haven’t explained the goals in natural or mathematical language which is leaving me to wonder why you are doing either sampling or replication (much less doing both within each iteration in the the function given to boot. )

— 
David

Sent from my iPhone

> On Dec 19, 2021, at 3:50 AM, varin sacha via R-help <r-help using r-project.org> wrote:
> 
> Dear R-experts,
> 
> Here below my R code working but really really slowly ! I need 2 hours with my computer to finally get an answer ! Is there a way to improve my R code to speed it up ? At least to win 1 hour ;=)
> 
> Many thanks
> 
> ########################################################
> library(boot)
> 
> s<- sample(178:798, 100000, replace=TRUE)
> mean(s)
> 
> N <- 1000
> out <- replicate(N, {
> a<- sample(s,size=5)
> mean(a)
> dat<-data.frame(a)
> 
> med<-function(d,i) {
> temp<-d[i,]
> f<-mean(temp)
> g<-var(replicate(50,mean(sample(temp,replace=T))))
> return(c(f,g))
> 
> }
> 
>   boot.out <- boot(data = dat, statistic = med, R = 10000)
>   boot.ci(boot.out, type = "stud")$stud[, 4:5]
> })
> mean(out[1,] < mean(s) & mean(s) < out[2,]) 
> ########################################################
> 
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