fastbayes:Bayesian modeling algorithms accelerated for particular model structures
General-purpose sampling approaches like Gibbs sampling are very useful for models that have not been studied extensively. But for some cases, specialized algorithms are available because of the model's commonality (e.g., linear regression) or niche popularity (e.g., Latent Dirichlet Allocation). This package is an effort to collect such algorithms in one place.
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| Versions[RSS] | 0.1.0.0,0.2.0.0 |
|---|---|
| Dependencies | base (>=4.6 && <4.8),hmatrix (>=0.16 && <0.17),vector (>=0.10 && <0.11) [details] |
| License | MIT |
| Copyright | Copyright (c) 2014 Melinae, Inc |
| Author | Chad Scherrer |
| Maintainer | chad.scherrer@gmail.com |
| Uploaded | byChadScherrer at2014-08-12T18:06:52Z |
| Category | Statistics |
| Home page | https://github.com/cscherrer/fastbayes |
| Source repo | head: git clonegit://github.com/cscherrer/fastbayes.git |
| Distributions | |
| Reverse Dependencies | 1 direct, 0 indirect [details] |
| Downloads | 1924 total (5 in the last 30 days) |
| Rating | (no votes yet)[estimated byBayesian average] |
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| Status | Docs available[build log] Successful builds reported[all 1 reports] |
Readme for fastbayes-0.2.0.0
[back to package description]fastbayes
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Installation
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Usage
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How to run tests
cabal configure --enable-tests && cabal build && cabal testContributing
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