RtoDPQ {distr}R Documentation

RtoDPQ

Description

function to do get empirical density, cumulative distribution and quantile function from random numbers

Usage

RtoDPQ(r, e = RtoDPQ.e, n = DefaultNrGridPoints)

Arguments

r the random number generator
e 10^e numbers are generated, a higher number leads to a better result.
n The number of grid points used to create the approximated functions, a higher number leads to a better result.

Details

RtoDPQ generates 10^e random numbers, by default

e = RtoDPQ.e

. The density is formed on the basis of n points using approxfun and density, by default

n = DefaultNrGridPoints

. The cumulative distribution function and the quantile function are also created on the basis of n points using approxfun and ecdf. Of course, the results are usually not exact as they rely on random numbers.

Value

RtoDPQ returns a list of functions.

dfun density
pfun cumulative distribution function
qfun quantile function

Note

Use RtoDPQ for absolutely continuous and RtoDPQ.d for discrete distributions.

Author(s)

Thomas Stabla Thomas.Stabla@uni-bayreuth.de,
Florian Camphausen Florian.Camphausen@uni-bayreuth.de,
Peter Ruckdeschel Peter.Ruckdeschel@uni-bayreuth.de,
Matthias Kohl Matthias.Kohl@uni-bayreuth.de

See Also

UnivariateDistribution-class

Examples

rn2 <- function(n){rnorm(n)^2}
x <- RtoDPQ(r = rn2, e = 4, n = 512)
# returns density, cumulative distribution and quantile function of
# squared standard normal distribution
x$dfun(4)
RtoDPQ(r = rn2, e = 5, n = 1024) # for a better result

rp2 <- function(n){rpois(n, lambda = 1)^2}
x <- RtoDPQ.d(r = rp2, e = 5)
# returns density, cumulative distribution and quantile function of
# squared Poisson distribution with parameter lambda=1

[Package distr version 1.5 Index]