Simulation over data repeatedly for four loops

Dear Contributors,

I am trying to perform a simulation over sample data,

but I need to reproduce the same simulation over 4 groups of data. My
ability with for loop is null, in particular related

to dimensions as I always get, no matter what I try,

"number of items to replace is not a multiple of replacement length"


This is what I intend to do: replicate this operation for

four times, where the index for the four groups is in the

part of the code: datiPc[[1]][,2].

I have to replicate the following code 4 times, where the

changing part is in the data from which I pick the sample,

the data that are stored in datiPc[[1]][,2].

If I had to use data for the four samples, I would substitute the 1 with a
j and replicate a loop four times, but it never worked.


My desired final outcome is a matrix with 10000 observations for each
couple of extracted samples, i.e. 8 columns of 10000 observations of means.



db<-c()

# Estrazione dei campioni dai dati di PGG e TRUST

estr1 <- c();

? ?estr2 <- c();

? ?m1<-c()

? ?m2<-c()

? ? ? tmp1<- data1[[1]][,2];

? ? ?tmp2<- data2[[2]][,2];

? ? ? ?for(i in 1:100){

estr1<-sample(tmp1, 1000, replace = TRUE)

? ? ? ?estr2<-sample(tmp2, 1000, replace = TRUE)


? ? ? ?m1[i]<-mean(estr1,na.rm=TRUE)

? ? ? ?m2[i]<-mean(estr2,na.rm=TRUE)

}

db<-data.frame(cbind(m1,m2))
Thanks for any help you can provide.
Best Regards

--

Francesca
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