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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

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This version
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0.3

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0.2.2

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0.2.1

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0.2

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Filename, size & hash SHA256 hash help File type Python version Upload date
multichain_mcmc-0.3.tar.gz (3.9 MB) Copy SHA256 hash SHA256 Source None Jun 21, 2010

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