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:
- Documentation: https://bayes_logistic.readthedocs.org.
- See related presentation video here.
