bbPrior                 Priors on model space for variable selection
                        problems
bestBIC                 Model with best AIC, BIC, EBIC or other general
                        information criteria (getIC)
bfnormmix               Number of Normal mixture components under
                        Normal-IW and Non-local priors
cil                     Treatment effect estimation for linear models
                        via Confounder Importance Learning using
                        non-local priors.
dalapl                  Density and random draws from the asymmetric
                        Laplace distribution
ddir                    Dirichlet density
diwish                  Density for Inverse Wishart distribution
dmom                    Non-local prior density, cdf and quantile
                        functions.
dpostNIW                Posterior Normal-IWishart density
eprod                   Expectation of a product of powers of Normal or
                        T random variables
icfit-class             Class "icfit"
icov                    Extract estimated inverse covariance
localnulltest           Local variable selection
marginalLikelihood      Marginal (or integrated) likelihood density of
                        the observed data for an individual model
                        handled by modelSelection (regression, GLM,
                        GAM, accelerated failure time, regression with
                        Normal, two-piece Normal, Laplace or two-piece
                        Laplace residuals
marginalNIW             Marginal likelihood under a multivariate Normal
                        likelihood and a conjugate Normal-inverse
                        Wishart prior.
mixturebf-class         Class "mixturebf"
modelSelection          Bayesian variable selection for generalized
                        linear and generalized additive models.
modelSelectionGGM       Bayesian variable selection for Gaussian
                        graphical models
msPriorSpec-class       Class "msPriorSpec"
msfit-class             Class "msfit"
msfit_ggm-class         Class "msfit_ggm"
plotprior               Plot estimated marginal prior inclusion
                        probabilities
postProb                Obtain posterior model probabilities
postSamples             Extract posterior samples from an object
priorp2g                Moment and inverse moment prior elicitation
rnlp                    Posterior sampling for regression parameters
