Package: BayesLN
Title: Bayesian Inference for Log-Normal Data
Version: 0.1.2
Authors@R: c(person("Aldo", "Gardini", email = "aldo.gardini2@unibo.it", role = c("aut", "cre")), 
            person("Enrico", "Fabrizi", role = c("aut")), 
            person("Carlo", "Trivisano", role = c("aut")))
Description: 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. 
Depends: R (>= 3.5.0)
Imports: optimx, ghyp, fAsianOptions, coda, Rcpp (>= 0.12.17), MASS,
        lme4, data.table
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, RcppArmadillo
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
Date: 2020-01-23
NeedsCompilation: yes
Packaged: 2020-02-11 18:54:27 UTC; aldog
Author: Aldo Gardini [aut, cre],
  Enrico Fabrizi [aut],
  Carlo Trivisano [aut]
Maintainer: Aldo Gardini <aldo.gardini2@unibo.it>
Repository: CRAN
Date/Publication: 2020-02-20 14:10:02 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 10:32:14 UTC; windows
Archs: i386, x64
