# flat.mix

0th

Percentile

##### 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

Keywords
distribution, arith
##### 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.

##### concept

• random sample
• image distribution
• absolutely continuous distribution
• utility

UnivariateDistribution-class, density, approxfun, ecdf

• flat.mix
##### 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)
Documentation reproduced from package distr, version 2.3.1, License: LGPL-3

### Community examples

Looks like there are no examples yet.