expect_mc_iid_ks: Test iid samples for correct cdf using KS test

In mcunit: Unit Tests for MC Methods

Description

Test if samples are behaving like an iid sample from a given CDF via the KS test and a sequential approach. Only works for continuous CDFs. Will report a warning if values are discrete

Usage

expect_mc_iid_ks(object, cdf, control = NULL)

Arguments

object	A function taking one argument - that generates n univariate iid samples.
cdf	A univariate cumulative distribution function, taking exactly one argument.
control	a list controlling the algorithm n number of samples to be taken in the first step. Default: 1e3 maxseqsteps: Number of sequential attempts to use. Default: 7. incn: Factor by which to multiply n from the second sequential attempt onward. Default: 4. level: bound on the type I error, ie the probability of wrongly rejecting a sampler with the correct distribution. Default: 1e-5. debug: If positive then debug information will be printed via 'message()'. Default: 0.

Value

The first argument, invisibly, to allow chaining of expectations.

Examples

   sampler <- function(n) rnorm(n)
   expect_mc_iid_ks(sampler, pnorm)

mcunit documentation built on April 2, 2021, 5:06 p.m.