BPS_PseudoBMA           Combine subset models wiht Pseudo-BMA
BPS_combine             Combine subset models wiht BPS
BPS_post_MvT            Perform the BPS sampling from posterior and
                        posterior predictive given a set of stacking
                        weights
BPS_postdraws_MvT       Compute the BPS posterior samples given a set
                        of stacking weights
BPS_pred_MvT            Compute the BPS spatial prediction given a set
                        of stacking weights
BPS_weights_MvT         Compute the BPS weights by convex optimization
CVXR_opt                Compute the BPS weights by convex optimization
arma_dist               Compute the Euclidean distance matrix
bayesMvLMconjugate      Gibbs sampler for Conjugate Bayesian
                        Multivariate Linear Models
conv_opt                Solver for Bayesian Predictive Stacking of
                        Predictive densities convex optimization
                        problem
d_pred_cpp_MvT          Evaluate the density of a set of unobserved
                        response with respect to the conditional
                        posterior predictive
dens_kcv_MvT            Compute the KCV of the density evaluations for
                        fixed values of the hyperparameters
dens_loocv_MvT          Compute the LOOCV of the density evaluations
                        for fixed values of the hyperparameters
expand_grid_cpp         Build a grid from two vector (i.e. equivalent
                        to 'expand.grid()' in 'R')
fit_cpp_MvT             Compute the parameters for the posteriors
                        distribution of beta and Sigma (i.e. updated
                        parameters)
forceSymmetry_cpp       Function to subset data for meta-analysis
models_dens_MvT         Return the CV predictive density evaluations
                        for all the model combinations
post_draws_MvT          Sample R draws from the posterior distributions
pred_bayesMvLMconjugate
                        Predictive sampler for Conjugate Bayesian
                        Multivariate Linear Models
predict.spBPS           Predict at new locations using a fitted spBPS
                        model
r_pred_cond_MvT         Draw from the conditional posterior predictive
                        for a set of unobserved covariates
r_pred_joint_MvT        Draw from the joint posterior predictive for a
                        set of unobserved covariates
r_pred_marg_MvT         Draw from the joint posterior predictive for a
                        set of unobserved covariates
sample_index            Function to sample integers (index)
spBPS                   Unified spatial BPS workflow (multivariate
                        path, works for q = 1)
spBPS_old               Unified spatial BPS workflow (multivariate
                        path, works for q = 1)
subset_data             Function to subset data for meta-analysis
