Default procedure to fill slots d,p,q given r for Lebesgue decomposed distributions
function to do get empirical density, cumulative distribution and quantile function from random numbers
RtoDPQ.LC(r, e = getdistrOption("RtoDPQ.e"), n = getdistrOption("DefaultNrGridPoints"))
- the random number generator
- $10^e$ numbers are generated, a higher number leads to a better result.
- The number of grid points used to create the approximated functions, a higher number leads to a better result.
RtoDPQ.LC generates $10^e$ random numbers, by default $$e = RtoDPQ.e$$.
Replicates are assumed to be part of the discrete part, unique values to be
part of the a.c. part of the distribution. For the replicated ones,
we generate a discrete distribution by a call to
The a.c. density is formed on the basis of $n$
points using approxfun and density (applied to the unique values), by default $$n = DefaultNrGridPoints$$.
The cumulative distribution function is based on all random variables,
and, as well as the quantile function, is also created on the basis of $n$ points using
ecdf. Of course, the results are usually not exact as they rely on random numbers.
RtoDPQ.LCreturns an object of class
RtoDPQ for absolutely continuous and
RtoDPQ.d for discrete distributions.
- random sample
- image distribution
- absolutely continuous distribution
rn2 <- function(n)ifelse(rbinom(n,1,0.3),rnorm(n)^2,rbinom(n,4,.3)) x <- RtoDPQ.LC(r = rn2, e = 4, n = 512) plot(x) # returns density, cumulative distribution and quantile function of # squared standard normal distribution d.discrete(x)(4) x2 <- RtoDPQ.LC(r = rn2, e = 5, n = 1024) # for a better result plot(x2)