Skip to main content

pymcmcstat

docs build coverage license zenodo joss pypi pyversion

The pymcmcstat package is a Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques:

  • Metropolis-Hastings (MH): Primary sampling method.

  • Adaptive-Metropolis (AM): Adapts covariance matrix at specified intervals.

  • Delayed-Rejection (DR): Delays rejection by sampling from a narrower distribution. Capable of n-stage delayed rejection.

  • Delayed Rejection Adaptive Metropolis (DRAM): DR + AM

This package is an adaptation of the MATLAB toolbox mcmcstat. The user interface is designed to be as similar to the MATLAB version as possible, but this implementation has taken advantage of certain data structure concepts more amenable to Python.

Note, advanced plotting routines are available in the mcmcplot package. Many plotting features are directly available within pymcmcstat, but some user’s may find mcmcplot useful.

Installation

This code can be found on the Github project page. This package is available on the PyPI distribution site and the latest version can be installed via

pip install pymcmcstat

The master branch on Github typically matches the latest version on the PyPI distribution site. To install the master branch directly from Github,

pip install git+https://github.com/prmiles/pymcmcstat.git

You can also clone the repository and run python setup.py install.

Getting Started

License

MIT

Contributors

See the GitHub contributor page

Citing pymcmcstat

Miles, (2019). pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis. Journal of Open Source Software, 4(38), 1417, https://doi.org/10.21105/joss.01417

Also, please cite the appropriate Zenodo archive for the version of pymcmcstat that you are using.

Feedback

Sponsor

This work was sponsored in part by the NNSA Office of Defense Nuclear Nonproliferation R&D through the Consortium for Nonproliferation Enabling Capabilities.

cnec

Metadata

Release files for pymcmcstat 1.9.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pymcmcstat 1.9.1
File Size Uploaded
pymcmcstat-1.9.1.tar.gz 109.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pymcmcstat 1.9.1
File Interpreter ABI Platform
pymcmcstat-1.9.1-py3-none-any.whl Python 3 none any Details

Total release size: 245.4 kB

Release files / pymcmcstat-1.9.1.tar.gz

Download URL pymcmcstat-1.9.1.tar.gz
Size 109.3 kB
Tags Source
SHA-256 checksum
How to use checksums
6ee8757b4f217e30f50bced09ca5367c83950bc4e7364eefd817b1f6fc3b806f
BLAKE2b-256 checksum
How to use checksums
2de0db63b20606e6bacc263f419bbc1f429109db04b55fe5a3d8e2ce3588dc3e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

Release files / pymcmcstat-1.9.1-py3-none-any.whl

Download URL pymcmcstat-1.9.1-py3-none-any.whl
Size 136.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
6cdf41a589a2b5c7097a743ee4a80f0ef053e7b742d2ed74dbfcc0c2441913a5
BLAKE2b-256 checksum
How to use checksums
d8f6eb38f6334f7a4dac529484dcd0279816a5e155c1a3f82d9d4940389d4940
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

Release history Release notifications | RSS feed

This release

1.9.1 This release

2 release files

1.9.0

2 release files

1.8.0

2 release files

1.7.1

2 release files

1.7.0

2 release files

1.6.0

2 release files

1.5.0

2 release files

1.4.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page