There may be better ways, but this should work:
R> p.yes <- 0.7
R> n.yes <- rbinom(1, nof.sample, p.yes)
R> n.no <- nof.sample - n.yes
R> dat.yes <- mydat[sample(which(mydat$Class == "yes"), n.yes,
replace=TRUE),]
R> dat.no <- mydat[sample(which(mydat$Class == "no"), n.no,
replace=TRUE),]
You can rbind() them, and shuffle the rows if you wish.
Andy
From: Muhammad Subianto>
> Dear all,
> Suppose I have a dataset like below, then I take for example,
> 100 random sample "class" variable where contains "yes"
and "no"
> respectively, 70% and 30%.
> I need a new 100 random sample from mydat dataset, but I
> can't get the result.
> Thanks you very much for any helps.
> Best, Muhammad Subianto
>
> mydat <- data.frame(size=c(30,12,15,10,12,12,25,30,20,14),
> A=c(0,1,0,1,0,1,1,1,0,0),
> B=c(1,1,0,1,0,1,1,0,0,1),
> C=c(0,0,1,1,0,0,1,1,0,0),
> D=c(1,1,1,1,0,1,0,0,1,1),
> E=c(1,1,0,1,1,1,1,1,1,0),
>
>
Class=c("yes","yes","no","yes","yes","no","yes","no","yes","yes"))
> mydat
> # Maximal data from dataset
> max.size <- sum(mydat$size);max.size
> # I need sample random
> nof.sample <- 100
> set.seed(123)
> sample.class <- sample(c("yes","no"), nof.sample,
prob=c(.7,
> .3), replace=TRUE) sample.class sampledat.class <-
> mydat[sample.class,] sampledat.class
>
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