Skip to main content

No project description provided

Project description

Python package that can be used to reproduce the figures and tables presented in Prado, E.B., Nemeth, C. & Sherlock, C. Metropolis-Hastings with Scalable Subsampling. arxiv (2024).

Project details


Download files

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

Source Distribution

pymhss-0.0.8.tar.gz (11.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pymhss-0.0.8-py3-none-any.whl (10.9 kB view details)

Uploaded Python 3

File details

Details for the file pymhss-0.0.8.tar.gz.

File metadata

  • Download URL: pymhss-0.0.8.tar.gz
  • Upload date:
  • Size: 11.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.6

File hashes

Hashes for pymhss-0.0.8.tar.gz
Algorithm Hash digest
SHA256 fbf27cfeb595ab1b7d92f54e9079b0b23d17aadf868edf600dbfd6f14e05f03e
MD5 573aa774dc4fd0a7d37da9e364965359
BLAKE2b-256 11503e9f29abe2501f2ee20594e42dcfdf3d73e836193e907c14e80b3e46cd8a

See more details on using hashes here.

File details

Details for the file pymhss-0.0.8-py3-none-any.whl.

File metadata

  • Download URL: pymhss-0.0.8-py3-none-any.whl
  • Upload date:
  • Size: 10.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.6

File hashes

Hashes for pymhss-0.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 19f1896ad2c19006f716b9ab53f7abffccf77131e65f3db102771ac8905af677
MD5 eb2ab0baa6ec44f180d54aa4813fd398
BLAKE2b-256 066954f66df6d36fb4d70fb78fe56260dd3e983053e43f0d5ab5db703fc2b604

See more details on using hashes here.

Supported by

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