mcunit (version 0.3.2)

expect_mc_iid_ks: Test iid samples for correct cdf using KS test

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

# NOT RUN {
   sampler <- function(n) rnorm(n)
   expect_mc_iid_ks(sampler, pnorm)
# }