LatentBMA: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"
<doi:10.48550/arXiv.2406.17318>. 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.
