10- Continuous empirical distribution

Continuous empirical distribution function

David J. Santana

25 de junio de 2016

ced function plots the empirical continuous function for a Poisson random sample
n= number of random values
lambda= Poisson parameter
seed = for reproducibility

ced=function(n,lambda,seed){
  set.seed(seed)
  rs=rpois(n,lambda)
  os=sort(rs)
  em=ecdf(os)
  xx=knots(em)
  if(min(xx)>0){xx=c(0,xx)}
  yy=c(0,em(xx))
  nen=length(xx)
  midxx=(xx[1:(nen-1)]+xx[2:nen])/2
  midxx=c(0,midxx,xx[nen])
  aux=1.1*xx[nen]
  plot(em,xlim=c(0,aux),
       main="Continuous empirical
       distribution function")
  lines(midxx,yy,col=2,lw=2)
  points(midxx,yy,col=3,pch=16)
  abline(v=midxx,col="lightgray",lt=2)
  abline(v=0,h=0,lw=2)
  xx=knots(em)
  paste("midpoints =",midxx,"Cedf =",yy)
}
#Example
seed=123
ced(10,5,seed)

## [1] "midpoints = 0 Cedf = 0"     "midpoints = 1 Cedf = 0"    
## [3] "midpoints = 3 Cedf = 0.1"   "midpoints = 4.5 Cedf = 0.3"
## [5] "midpoints = 6 Cedf = 0.6"   "midpoints = 7.5 Cedf = 0.7"
## [7] "midpoints = 8.5 Cedf = 0.9" "midpoints = 9 Cedf = 1"