Unit testing for Monte Carlo methods, particularly Markov Chain Monte Carlo (MCMC) methods, are implemented as extensions of the 'testthat' package. The MCMC methods check whether the MCMC chain has the correct invariant distribution. They do not check other properties of successful samplers such as whether the chain can reach all points, i.e. whether is recurrent. The tests require the ability to sample from the prior and to run steps of the MCMC chain. The methodology is described in Gandy and Scott (2020) <arXiv:2001.06465>.
|Depends:||R (≥ 3.1)|
|Imports:||testthat (≥ 2.3), stats, rlang, Rdpack (≥ 0.7), methods, simctest (≥ 2.6)|
|Author:||Axel Gandy [aut, cre], James Scott [aut]|
|Maintainer:||Axel Gandy <a.gandy at imperial.ac.uk>|
|CRAN checks:||mcunit results|
Introduction to mcunit
Checking Levels of Tests or Coverage Probabilities of CIs
|Windows binaries:||r-devel: mcunit_0.3.2.zip, r-release: mcunit_0.3.2.zip, r-oldrel: mcunit_0.3.2.zip|
|macOS binaries:||r-release (arm64): mcunit_0.3.2.tgz, r-oldrel (arm64): mcunit_0.3.2.tgz, r-release (x86_64): mcunit_0.3.2.tgz, r-oldrel (x86_64): mcunit_0.3.2.tgz|
|Old sources:||mcunit archive|
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