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pymcmcstat

pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis - Published in JOSS (2019)

https://github.com/prmiles/pymcmcstat

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 6 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • ✓
    Committers with academic emails
    2 of 3 committers (66.7%) from academic institutions
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

adaptive-metropolis delayed-rejection markov-chain-monte-carlo mcmc metropolis-hastings python

Scientific Fields

Economics Social Sciences - 85% confidence
Mathematics Computer Science - 65% confidence
Last synced: 4 months ago · JSON representation

Repository

Python implementation of MATLAB toolbox "mcmcstat"

Basic Info
Statistics
  • Stars: 72
  • Watchers: 2
  • Forks: 11
  • Open Issues: 5
  • Releases: 23
Topics
adaptive-metropolis delayed-rejection markov-chain-monte-carlo mcmc metropolis-hastings python
Created about 8 years ago · Last pushed over 3 years ago
Metadata Files
Readme Changelog Contributing License Code of conduct

README.rst 

`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
===============

- `Tutorial notebooks `_
- `Documentation `_
- `Release history `_
- `Contributing guidelines `_

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
========

- `Feature Request `_
- `Bug Report `_

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|

   
.. |docs| image:: https://readthedocs.org/projects/pymcmcstat/badge/?version=latest
    :target: https://pymcmcstat.readthedocs.io/en/latest/?badge=latest
    
.. |build| image:: https://travis-ci.org/prmiles/pymcmcstat.svg?branch=master
    :target: https://travis-ci.org/prmiles/pymcmcstat
    
.. |license| image:: https://img.shields.io/badge/License-MIT-yellow.svg
    :target: https://github.com/prmiles/pymcmcstat/blob/master/LICENSE.txt

.. |coverage| image:: https://coveralls.io/repos/github/prmiles/pymcmcstat/badge.svg
    :target: https://coveralls.io/github/prmiles/pymcmcstat

.. |zenodo| image:: https://zenodo.org/badge/107596954.svg
    :target: https://zenodo.org/badge/latestdoi/107596954
    
.. |pypi| image:: https://img.shields.io/pypi/v/pymcmcstat.svg
    :target: https://pypi.org/project/pymcmcstat/
    
.. |pyversion| image:: https://img.shields.io/pypi/pyversions/pymcmcstat.svg
    :target: https://pypi.org/project/pymcmcstat/

.. |cnec| image:: https://raw.githubusercontent.com/prmiles/pymcmcstat/master/doc/cnec-logo.png
    :target: https://cnec.ncsu.edu/

.. |joss| image:: http://joss.theoj.org/papers/10.21105/joss.01417/status.svg
    :target: https://doi.org/10.21105/joss.01417

Owner

  • Name: Paul Miles
  • Login: prmiles
  • Kind: user

JOSS Publication

pymcmcstat: A Python Package for Bayesian Inference Using Delayed Rejection Adaptive Metropolis
Published
June 06, 2019
DOI
Volume 4, Issue 38, Page 1417
Authors
Paul R. Miles ORCID
Department of Mathematics, North Carolina State University
Editor
Kathryn Huff ORCID
Tags
MCMC DRAM Bayesian Inference
View PDF Review Thread Software Archive

GitHub Events

Total
  • Watch event: 1
  • Issue comment event: 1
  • Fork event: 1
Last Year
  • Watch event: 1
  • Issue comment event: 1
  • Fork event: 1

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 876
  • Total Committers: 3
  • Avg Commits per committer: 292.0
  • Development Distribution Score (DDS): 0.011
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
prmiles p****s@n****u 866
prmiles p****v@g****m 9
pmilescs p****b@m****u 1
Committer Domains (Top 20 + Academic)
my.fsu.edu: 1 ncsu.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 24
  • Total pull requests: 76
  • Average time to close issues: 6 months
  • Average time to close pull requests: 1 day
  • Total issue authors: 11
  • Total pull request authors: 1
  • Average comments per issue: 0.96
  • Average comments per pull request: 0.66
  • Merged pull requests: 75
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • prmiles (13)
  • djmitche (2)
  • isa-a (1)
  • katyhuff (1)
  • Huzaifg (1)
  • XiaoyuHy (1)
  • mwkury (1)
  • rayadastidar (1)
  • mikepab (1)
  • mcekwonu (1)
  • nccreang (1)
Pull Request Authors
  • prmiles (76)
Top Labels
Issue Labels
enhancement (12) bug (7) question (2)
Pull Request Labels
bug (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 159 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 10
  • Total maintainers: 1
pypi.org: pymcmcstat

A library to perform MCMC simulations using DRAM

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 159 Last month
  • Docker Downloads: 0
Rankings
Docker downloads count: 2.5%
Stargazers count: 8.8%
Dependent packages count: 9.8%
Forks count: 10.9%
Average: 11.2%
Downloads: 13.1%
Dependent repos count: 21.8%
Maintainers (1)
prmiles
Last synced: 4 months ago

Dependencies

requirements.txt pypi
  • coveralls *
  • deprecated >=1.2.6
  • h5py >=2.7.0
  • mcmcplot >=1.0.1
  • numpy >=1.14
  • scipy >=1.0
  • sphinx_rtd_theme *
  • sphinxcontrib-bibtex *
  • statsmodels >=0.9.0
setup.py pypi
  • deprecated >=1.2.6
  • h5py >=2.7.0
  • mcmcplot >=1.0.1
  • numpy >=1.14
  • scipy >=1.0
  • statsmodels >=0.9.0