sl4bayesmeta: Sensitivity and learning: Project Home – R-Forge

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

• Natural Language : English
• Programming Language : R

Registered: 2019-08-15 12:39
Activity Ranking: 0
View project Statistics
View list of RSS feeds available for this project.

Project Admins

View the 2 Member(s)

Request to join