pieter claassen wrote: > I am trying to understand what rbinom function does. > > Here is some sample code. Are both the invocations of bfunc effectively > doing the same or I am missing the point? > > There are some "newbie" issues with your code (you are extending a on every iteration, and your bfunc is just rbinom with the parameters in a different order), but basically, yes: They are conceptually the same. Both give 10000 independent binomial samples.
In fact, if you reset the random number generator in between, they also give the same results (this is an implementation issue and not obviously guaranteed for any distribution) . Here's an example with smaller values than 10000 and 30. > set.seed(123) > rbinom(10,1,.5) [1] 0 1 0 1 1 0 1 1 1 0 > set.seed(123) > for (i in 1:10) print(rbinom(1,1,.5)) [1] 0 [1] 1 [1] 0 [1] 1 [1] 1 [1] 0 [1] 1 [1] 1 [1] 1 [1] 0 > set.seed(123) > replicate(10, rbinom(1,1,.5)) [1] 0 1 0 1 1 0 1 1 1 0 > Thanks, > Pieter > > bfunc <- function(n1,p1,sims) { > c<-rbinom(sims,n1,p1) > c > } > > a=c() > b=c() > p1=.5 > for (i in 1:10000){ > a[i]=bfunc(30,p1,1) > } > b=bfunc(30,p1,10000) > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.