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Functionality for posterior inference, sensitivity and learning quantification in the Bayesian normalnormal hierarchical model used for Bayesian metaanalysis. Provides functions for heterogeneity prior adjustment with respect to tails or the latent model complexity for halfnormal (HN), halfCauchy (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 


Author  Manuela Ott [aut, cre], Malgorzata Roos [aut], 
Maintainer  Manuela Ott <[email protected]> 
License  GPL (>=2) 
Version  0.21 
Package repository  View on RForge 
Installation 
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