sl4bayesmeta: Sensitivity and learning for Bayesian meta-analysis

Functionality for posterior inference, sensitivity and learning quantification in the Bayesian normal-normal hierarchical model used for Bayesian meta-analysis. Provides functions for heterogeneity prior adjustment with respect to tails or the latent model complexity for half-normal (HN), half-Cauchy (HC), exponential (EXP) and Lomax (LMX) priors. The functions operate on data sets which are compatible with the bayesmeta R package on CRAN.

Package details

AuthorManuela Ott [aut, cre], Malgorzata Roos [aut],
MaintainerManuela Ott <>
LicenseGPL (>=2)
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("sl4bayesmeta", repos="")

Try the sl4bayesmeta package in your browser

Any scripts or data that you put into this service are public.

sl4bayesmeta documentation built on Feb. 18, 2020, 3:02 p.m.