r - how to to write a function that demonstrates the central limit theorem with graphics -


i'm trying write function creates animated graphics(without using animation package) users can control inputs(sample size , distribution ect..) demonstrates central limit theorem. in theory want having trouble writing function users can control inputs mentioned above. 

msample <- na # set empty vector ns <-3 # sample size for(i in 1:500){ sam <- runif(ns) * 10 # draw sample  msample[i] <- mean(sam) # save mean of sample h <- hist(msample, breaks=seq(0,10, len=50), # histogram of means xlim=c(0,10), col=grey(.9), xlab="", main="central limit theorem", border="blue", las=1) points(sam, rep(max(h$count), length(sam)), pch=16, col=grey(.2)) # add sampled values points(msample[i], max(h$count), # add sample mean value col="red", pch=15) text(10, max(h$count), paste("sample no", i)) hist(msample[i], breaks=seq(0,10, len=50), # ovelay sample mean  xlim=c(0,10), col="red", add=t, # in histogram xlab="", border="white", las=1) sys.sleep(.05) }

it not clear want result. think, can put code in function , use dot argument ... solution give parameters (distribution parameters example).

   central.simul <- function(n, ns,type = c("runif", "rnorm", "rbinom"),...){         type <- match.arg(type)         msample <- rep(na,n)  ## edit here: intialisation         for(i in 1:n){           sam <- switch(type,                         runif = runif(ns)*10,                         rnorm = rnorm(ns)*10,                         rbinom = rbinom(ns,...))           msample[i] <- mean(sam) # save mean of sample           add.hist <- > 1           h <- hist(msample, breaks=seq(0,10, len=50), # histogram of means                     xlim=c(0,10), col=grey(.9),                     xlab="", main="central limit theorem", border="blue", las=1,add=add.hist)           points(sam, rep(max(h$count), length(sam)),                  pch=16, col=grey(.2)) # add sampled values           points(msample[i], max(h$count), # add sample mean value                  col="red", pch=15)           text(10, max(h$count), paste0("sample no ", i))           hist(msample[i], breaks=seq(0,10, len=50), # ovelay sample mean                 xlim=c(0,10), col="red", add=t, # in histogram                xlab="", border="white", las=1)           sys.sleep(.1)         }     }

you can call using :

central.simul(10,3,'runif') central.simul(10,3,'rbinom',size=2,prob=0.5)

the code don't work rnorm example ( should modify breaks think), should start.


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