sl4bayesmeta: Sensitivity and learning for the 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 <[email protected]>
LicenseGPL (>=2)
Version0.2-1
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("sl4bayesmeta", repos="http://R-Forge.R-project.org")

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sl4bayesmeta documentation built on Dec. 3, 2019, 3 a.m.