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mcunit  

Unit Tests for MC Methods
View on CRAN: Click here


Download and install mcunit package within the R console
Install from CRAN:
install.packages("mcunit")

Install from Github:
library("remotes")
install_github("cran/mcunit")

Install by package version:
library("remotes")
install_version("mcunit", "0.3.2")



Attach the package and use:
library("mcunit")
Maintained by
Axel Gandy
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-05
Latest Update: 2021-04-02
Description:
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) .
How to cite:
Axel Gandy (2020). mcunit: Unit Tests for MC Methods. R package version 0.3.2, https://cran.r-project.org/web/packages/mcunit. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.3.1 (2020-03-05 12:10)
Other packages that cited mcunit R package
View mcunit citation profile
Other R packages that mcunit depends, imports, suggests or enhances
Complete documentation for mcunit
Functions, R codes and Examples using the mcunit R package
Some associated functions: expect_bernoulli . expect_mc_iid_chisq . expect_mc_iid_ks . expect_mc_iid_mean . expect_mc_test . expect_mcmc . expect_mcmc_reversible . mcunit-package . 
Some associated R codes: MCUnit-package.R . expect_invariant.R . expect_mc.R . expect_simctest.R .  Full mcunit package functions and examples
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