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This package will fit Bayesian logistic regression models with arbitrary prior means and covariance matrices, although we work with the inverse covariance matrix which is the log-likelihood Hessian.

Either the full Hessian or a diagonal approximation may be used.

Individual data points may be weighted in an arbitrary manner.

Finally, p-values on each fitted parameter may be calculated and this can be used for variable selection of sparse models.

• Free software (BSD):
• Documentation: https://bayes_logistic.readthedocs.org.
• See related presentation video here.

Example Notebook