Metadata-Version: 2.1
Name: conjugate-bayes
Version: 0.0.1
Summary: Conjugate Bayesian linear regression and distribution models in Python..
Home-page: https://github.com/tonyduan/conjugate-bayes
Author: Tony Duan
Author-email: tonyduan@cs.stanford.edu
License: UNKNOWN
Description: ### Conjugate Bayesian Models
        
        Last update: June 2019.
        
        ---
        
        Lightweight Python library implementing a few conjugate Bayesian models. For details on the derivations see [1].
        
        ```
        pip3 install conjugate-bayes
        ```
        
        We support the following:
        
        #### To fit distribution models
        
        - Beta-Bernoulli
        - Gamma-Poisson
        - Normal-Inverse-Gamma
        
        #### To fit regression models
        
        - Linear regression with Normal Inverse-Gamma prior
        - Linear regression with Zellner's *g*-prior
        
        #### Future work
        
        - Dirichlet-Multinomial
        - Normal-Inverse-Wishart
        
        #### Usage
        
        Below we show an example fitting a simple Bayesian linear regression with unknown beta and unknown variance.
        
        ```python
        model = NIGLinearRegression(mu=np.zeros(2), v=100*np.eye(2), a=0.5, b=0.5)
        model.fit(x_tr, y_tr)
        
        sigma2 = model.get_marginal_sigma2()
        beta = model.get_conditional_beta(sigma2=sigma2.mean())
        ```
        
        The above example results in the following prediction intervals.
        
        ![ex_model](examples/ex.png)
        
        For further details the `examples/` folder.
        
        #### References
        
        [1] P. D. Hoff, A First Course in Bayesian Statistical Methods (New York: Springer-Verlag, 2009).
        
        #### License
        
        This library is available under the MIT License.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
