https://github.com/tpapp/mcmc_lr_tests.jl

Likelihood ratio test for comparing MCMC sample means to a known value.
https://github.com/tpapp/mcmc_lr_tests.jl

Last synced: 4 months ago
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Likelihood ratio test for comparing MCMC sample means to a known value.

• Host: GitHub
• URL: https://github.com/tpapp/mcmc_lr_tests.jl
• Owner: tpapp
• License: other
• Created: 2017-07-22T14:41:55.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2020-12-20T09:16:40.000Z (over 5 years ago)
• Last Synced: 2026-01-20T20:05:02.687Z (5 months ago)
• Language: Julia
• Size: 11.7 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# MCMC\_LR\_Test

[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](http://www.repostatus.org/badges/latest/wip.svg)](http://www.repostatus.org/#wip)

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[![codecov.io](http://codecov.io/github/tpapp/MCMC_LR_Tests.jl/coverage.svg?branch=master)](http://codecov.io/github/tpapp/MCMC_LR_Tests.jl?branch=master)

Compare the mean and covariance of a MCMC sample to a known value using a likelihood ratio test with a p-value.

For unit testing *MCMC software*. The returned p-values should be treated as a distance measure that has a distribution that is not too far away from the uniform, but the latter is not guaranteed. Simple testing can assert that p-values are bigger than a certain threshold, more complex testing can compare quantiles. See the docstrings of the exported functions `mean_LR_pvalue` and `cov_LR_pvalue`, and the unit tests.

## References

Bai, Z., Jiang, D., Yao, J. F., & Zheng, S. (2009). Corrections to LRT on large-dimensional covariance matrix by RMT. The Annals of Statistics, 3822-3840.

Vats, D., Flegal, J. M., & Jones, G. L. (2015). Multivariate output analysis for Markov chain Monte Carlo. arXiv preprint [arXiv:1512.07713](https://arxiv.org/abs/1512.07713).