flat.mix {distr}

Default procedure to fill slots d,p,q given r for Lebesgue decomposed distributions

Description

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

Usage

flat.mix(object)

Arguments

object

object of class UnivariateMixingDistribution

Details

flat.mix 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 DiscreteDistribution. 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 approxfun and ecdf. Of course, the results are usually not exact as they rely on random numbers.

Value

flat.mix returns an object of class UnivarLebDecDistribution.

Note

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

Author(s)

Peter Ruckdeschel [e-mail]

See Also

UnivariateDistribution-class, density, approxfun, ecdf

Examples

D1 <- Norm()
D2 <- Pois(1)
D3 <- Binom(1,.4)
D4 <- UnivarMixingDistribution(D1,D2,D3, mixCoeff = c(0.4,0.5,0.1), 
      withSimplify = FALSE)
D <- UnivarMixingDistribution(D1,D4,D1,D2, mixCoeff = c(0.4,0.3,0.1,0.2), 
      withSimplify = FALSE)
D
D0<-flat.mix(D)
D0
plot(D0)