RtoDPQ {distr} | R Documentation |
function to do get empirical density, cumulative distribution and quantile function from random numbers
RtoDPQ(r, e = getdistrOption("RtoDPQ.e"), n = getdistrOption("DefaultNrGridPoints"))
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. |
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.
RtoDPQ
returns a list of functions.
dfun |
density |
pfun |
cumulative distribution function |
qfun |
quantile function |
Use RtoDPQ
for absolutely continuous and RtoDPQ.d
for discrete distributions.
Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel Peter.Ruckdeschel@itwm.fraunhofer.de,
Matthias Kohl Matthias.Kohl@stamats.de
UnivariateDistribution-class
,
density
,
approxfun
,
ecdf
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