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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. WWW: http://pypi.python.org/pypi/pymc/ PR: ports/129567 Submitted by: Wen Heping <wenheping at gmail.com>
12 lines
554 B
Plaintext
12 lines
554 B
Plaintext
Bayesian estimation, particularly using Markov chain Monte
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Carlo (MCMC), is an increasingly relevant approach to
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statistical estimation. However, few statistical software
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packages implement MCMC samplers, and they are non-trivial
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to code by hand. pymc is a python package that implements
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the Metropolis-Hastings algorithm as a python class, and is
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extremely flexible and applicable to a large suite of problems.
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pymc includes methods for summarizing output, plotting,
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goodness-of-fit and convergence diagnostics.
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WWW: http://pypi.python.org/pypi/pymc/
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