BayesLN - Bayesian Inference for Log-Normal Data
Bayesian inference under log-normality assumption must be
performed very carefully. In fact, under the common priors for
the variance, useful quantities in the original data scale
(like mean and quantiles) do not have posterior moments that
are finite (Fabrizi et al. 2012 <doi:10.1214/12-BA733>). This
package allows to easily carry out a proper Bayesian
inferential procedure by fixing a suitable distribution (the
generalized inverse Gaussian) as prior for the variance.
Functions to estimate several kind of means (unconditional,
conditional and conditional under a mixed model) and quantiles
(unconditional and conditional) are provided.
