#' @title Binomial Simulation
#'
#' @description Shows how to simulate a Binomial
#'
#' @details More details about the function
#'
#' @param iter Number of iterations
#' @param n Number of Bernoulli trials
#' @param p Probability of a success
#'
#' @importFrom grDevices rainbow
#' @importFrom graphics barplot
#'
#' @return Barplot and table of relative frequencies
#' @export
#'
#' @examples
#' mybin() # Use default values
mybin=function(iter=100,n=10, p=0.5){
# make a matrix to hold the samples
#initially filled with NA's
sam.mat=matrix(NA,nrow=n,ncol=iter, byrow=TRUE)
#Make a vector to hold the number of successes in each trial
succ=vector(mode="numeric", length=iter)
for( i in 1:iter){
#Fill each column with a new sample
sam.mat[,i]=sample(c(1,0),n,replace=TRUE, prob=c(p,1-p))
#Calculate a statistic from the sample (this case it is the sum)
succ[i]=sum(sam.mat[,i])
}
#Make a table of successes
succ.tab=table(factor(succ,levels=0:n))
#Make a barplot of the proportions
barplot(succ.tab/(iter), col=rainbow(n+1), main="Binomial simulation", xlab="Number of successes")
succ.tab/iter
}
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