Bayesian Model Averaging for Univariate Link Latent Gaussian Models

Bayesian model averaging (BMA) algorithms for univariate link latent Gaussian models (ULLGMs). For detailed information, refer to Steel M.F.J. & Zens G. (2024) "Model Uncertainty in Latent Gaussian Models with Univariate Link Function" . The package supports various g-priors and a beta-binomial prior on the model space. It also includes auxiliary functions for visualizing and tabulating BMA results. Currently, it offers an out-of-the-box solution for model averaging of Poisson log-normal (PLN) and binomial logistic-normal (BiL) models. The codebase is designed to be easily extendable to other likelihoods, priors, and link functions.


Reference manual

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install.packages("LatentBMA")

0.1.3 by Gregor Zens, 5 months ago


Browse source code at https://github.com/cran/LatentBMA


Authors: Gregor Zens [aut, cre] , Mark F.J. Steel [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports ggplot2, knitr, mnormt, progress, reshape2

Suggests rmarkdown


See at CRAN