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BayesLN  

Bayesian Inference for Log-Normal Data
View on CRAN: Click here


Download and install BayesLN package within the R console
Install from CRAN:
install.packages("BayesLN")

Install from Github:
library("remotes")
install_github("cran/BayesLN")

Install by package version:
library("remotes")
install_version("BayesLN", "0.2.10")



Attach the package and use:
library("BayesLN")
Maintained by
Aldo Gardini
[Scholar Profile | Author Map]
First Published: 2020-02-20
Latest Update: 2022-10-26
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 ). 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.
How to cite:
Aldo Gardini (2020). BayesLN: Bayesian Inference for Log-Normal Data. R package version 0.2.10, https://cran.r-project.org/web/packages/BayesLN. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.2 (2020-02-20 15:10), 0.2.1 (2020-10-28 11:40), 0.2.2 (2021-03-31 12:00), 0.2.3 (2022-04-11 16:02), 0.2.6 (2022-05-02 13:30), 0.2.8 (2022-10-26 12:48)
Other packages that cited BayesLN R package
View BayesLN citation profile
Other R packages that BayesLN depends, imports, suggests or enhances
Complete documentation for BayesLN
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