R/PoissonSample.R

Defines functions mycltp

Documented in mycltp

#' Poisson Sample
#'
#' @param n sample size
#' @param iter iterations
#' @param lambda exponential value in poisson distribution
#' @param ...
#'
#' @return
#' @export
#'
#' @examples
#' \dontrun mycltp(n=10,iter=10000,lambda=10)
mycltp=function(n,iter,lambda=10,...){

  y=rpois(n*iter,lambda=lambda)
  data=matrix(y,nr=n,nc=iter,byrow=TRUE)
  w=apply(data,2,mean)

  param=hist(w,plot=FALSE)


  ymax=max(param$density)

  ymax=1.1*ymax


  layout(matrix(c(1,1,2,3),nr=2,nc=2, byrow=TRUE))


  hist(w,freq=FALSE,  ylim=c(0,ymax), col=rainbow(max(w)),
       main=paste("Histogram of sample mean","\n", "sample size= ",n," iter=",iter," lambda=",lambda,sep=""),
       xlab="Sample mean",...)

  lines(density(w),col="Blue",lwd=3)

  curve(dnorm(x,mean=lambda,sd=sqrt(lambda/n)),add=TRUE,col="Red",lty=2,lwd=3)

  barplot(table(y)/(n*iter),col=rainbow(max(y)), main="Barplot of sampled y", ylab ="Rel. Freq",xlab="y" )
  x=0:max(y)
  plot(x,dpois(x,lambda=lambda),type="h",lwd=5,col=rainbow(max(y)),
       main="Probability function for Poisson", ylab="Probability",xlab="y")
}
ake0002/ForReal documentation built on Nov. 21, 2020, 9:11 a.m.