pybalonor: A package for the Bayesian analysis of the log-normal distribution in Python.

This Python package helps to perform a Bayesian analysis of log-normally distributed data (PYthon package for Bayesian Analysis of the LOg-NORmal distribution). Performing a Bayesian analysis of log-normally distributed data requires care in the prior choice to yield posterior predictive distributions with finite moments (e.g. Fabrizi & Trivisano, 2012). This package uses a simple uniform prior for the log-location and log-variance parameter. The problem of normalizing the posterior of the mean is solved by imposing a finite upper bound on the log-variance parameter. If you are looking for an analysis of the log-normal distribution, you might likely want to check out the R package BayesLN by Gardini, Fabrizi, and Trivisano. Their conjugate prior is more sophisticated than the flat prior of pybalonor, and, from limited analysis, seems to lead to tighter posterior bounds