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 |
| Category | Statistics |
| Home page | https://github.com/cscherrer/fastbayes |
| Source repo | head: git clone git://github.com/cscherrer/fastbayes.git |
| Uploaded | by ChadScherrer at 2014-08-12T18:06:52Z |
| Distributions | |
| Reverse Dependencies | 1 direct, 0 indirect [details] |
| Downloads | 1834 total (6 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs available [build log] Successful builds reported [all 1 reports] |