Added functions for computing the logarithm of the marginal likelihood of a GLM under all priors implemented in the package.
Updated the implementation of commensurate prior to be fully Bayesian.
Updated the implementation of robust meta-analytic predictive
prior (RMAP) from using a Gaussian mixture model to approximate the MAP
prior to computing the updated mixture weights based on marginal
likelihoods. Specifically, we removed glm.rmap.bhm() and
glm.rmap.bhm.approx() functions. The posterior samples from
using the RMAP now can be obtained via calling glm.rmap()
function directly.
Added function for sampling from the posterior distribution of a GLM under a normal/half-normal prior.
Added the vignette “AIDS_Progression”.
Updated Stan files for NAPP and NPP by eliciting priors on logit(a0) instead of a0.
Added two data sets: E1684 and E1690.
Fixed bugs in checking input offset.list for
glm.leap().
Fixed bugs in computing normalizing constants for normal and
Gamma models using glm.npp.lognc().
Fixed bugs in renaming/reordering output variables in
glm.bhm().