SCM

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

Project description

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.

Project Information

Registered: 2019-08-15 12:39
Activity Ranking: 24
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