bmcmc
An MCMC package for Bayesian data analysis
bmcmc is a general purpose mcmc package which should be useful for Bayesian data analysis. It uses an adaptive scheme for automatic tuning of proposal distributions. It can also handle hierarchical Bayesian models via Metropolis-Within-Gibbs scheme.
Documentation
For latest documentation see here.
1 maintainer
Metadata
1 maintainer
Release files for bmcmc 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bmcmc-0.1.0.tar.gz | 9.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bmcmc-0.1.0-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 18.5 kB
Release files / bmcmc-0.1.0.tar.gz
| Download URL | bmcmc-0.1.0.tar.gz |
|---|---|
| Size | 9.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / bmcmc-0.1.0-py2-none-any.whl
| Download URL | bmcmc-0.1.0-py2-none-any.whl |
|---|---|
| Size | 9.2 kB |
| Tags | Python 2 |
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SHA-256 checksum How to use checksums |
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