Skip to main content

Multichain MCMC framework and algorithms

Project description

A simple framework based on PyMC for multichain MCMC algorithms.

Contains working implementations of:
  • DREAM/DREAM_ZS sampler : multichain_mcmc.dream.DreamSampler

  • Adaptive Metropolis Adjusted Langevin Algorithm (AMALA) sampler : multichain_mcmc.amala.AmalaSampler

See the sampler classes for details. AMALA sampler requires PyMC branch with gradient information support to function.

http://github.com/pymc-devs/pymc/tree/gradientBranch

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

multichain_mcmc-0.3.tar.gz (3.9 MB view hashes)

Uploaded Source

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