Skip to main content

Marginal Likelihood estimation via Permutation counting

Project description

perms

The perms package implements the algorithm proposed by [1] for computing marginal likelihoods via permutation counting.

References

[1] Christensen, D (2023). "Inference for Bayesian Nonparametric Models with Binary Response Data via Permutation Counting." Bayesian Anal. 19 (1) 293 - 318, March 2024. https://doi.org/10.1214/22-BA1353

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

perms-1.21.tar.gz (77.8 kB view details)

Uploaded Source

File details

Details for the file perms-1.21.tar.gz.

File metadata

  • Download URL: perms-1.21.tar.gz
  • Upload date:
  • Size: 77.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for perms-1.21.tar.gz
Algorithm Hash digest
SHA256 5c0639f99488fddf3f4aae44167e421aa9e80899bedff075040c38f573c38ead
MD5 0a3b981c215a3ad65cd81ed62b3c5e13
BLAKE2b-256 e3f97f115b84e6e4c5c43ca8d2b0bb272b1522632d88546af765e39ba0b58599

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