Markov Chain Monte Carlo sampling toolkit.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Colin.Carroll from gravatar.com Colin.Carroll Avatar for fonnesbeck from gravatar.com fonnesbeck Avatar for id.mosthege.net from gravatar.com id.mosthege.net Avatar for Thomas.Wiecki from gravatar.com Thomas.Wiecki

Unverified details

These details have not been verified by PyPI
Meta
Classifiers

Project description

Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC),

is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. pymc is a python package that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. pymc includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.

pymc only requires NumPy. All other dependencies such as matplotlib, SciPy, pytables, sqlite or mysql are optional.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Colin.Carroll from gravatar.com Colin.Carroll Avatar for fonnesbeck from gravatar.com fonnesbeck Avatar for id.mosthege.net from gravatar.com id.mosthege.net Avatar for Thomas.Wiecki from gravatar.com Thomas.Wiecki

Unverified details

These details have not been verified by PyPI
Meta
Classifiers

Release history Release notifications | RSS feed

5.18.0

5.17.1 yanked

Reason this release was yanked:

It was a mistake, supposed to be 5.18.

5.17.0

5.16.2

5.16.1

5.16.0

5.15.1

5.15.0

5.14.0

5.13.1

5.13.0

5.12.0

5.11.0

5.10.4

5.10.3

5.10.2

5.10.1

5.10.0

5.9.2

5.9.1

5.9.0

5.8.2

5.8.1

5.8.0

5.7.2

5.7.1

5.7.0

5.6.1

5.6.0

5.5.0

5.4.1

5.4.0

5.3.1

5.3.0

5.2.0

5.1.2

5.1.1

5.1.0

5.0.2

5.0.1

5.0.0

4.4.0

4.3.0

4.2.2

4.2.1

4.2.0

4.1.7

4.1.6

4.1.5

4.1.4

4.1.3

4.1.2

4.1.1

4.1.0

4.0.1

4.0.0

4.0.0b6 pre-release

4.0.0b5 pre-release

4.0.0b4 pre-release

4.0.0b3 pre-release

4.0.0b2 pre-release

4.0.0b1 pre-release

2.3.8

2.3.6

2.3.5

2.3.4

2.3.3

2.3.2

This version

2.3.1

2.3

2.2

2.1beta pre-release

2.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pymc-2.3.1.tar.gz (370.2 kB view details)

Uploaded Source

Built Distribution

pymc-2.3.1-py2.7-macosx-10.9-intel.egg (1.0 MB view details)

Uploaded Source

File details

Details for the file pymc-2.3.1.tar.gz.

File metadata

  • Download URL: pymc-2.3.1.tar.gz
  • Upload date:
  • Size: 370.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pymc-2.3.1.tar.gz
Algorithm Hash digest
SHA256 6d21bc8e818469e00e75db8f30b92b05817169f65b8a9f9f2025bf14b9933cf0
MD5 66102a39b95efc9f9438803cdc93df4f
BLAKE2b-256 9be19a58bcd19a000191222b4dd42d71f9732b6c314dad076dba0430a3f0a86a

See more details on using hashes here.

File details

Details for the file pymc-2.3.1-py2.7-macosx-10.9-intel.egg.

File metadata

File hashes

Hashes for pymc-2.3.1-py2.7-macosx-10.9-intel.egg
Algorithm Hash digest
SHA256 d87a9dc71285437b6d11616dee88f682f93bcddddb324482de9a8f089abcefff
MD5 43cd4219dbf36f03210d462ba9998915
BLAKE2b-256 ea846f80acee72d8f1ff327a35b643c7eac8033ae5234dd1f323dd2194ed4f18

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page