# Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

## Documentation for package ‘spBPS’ version 0.0-4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

arma_dist | Compute the Euclidean distance matrix
bayesMvLMconjugate | Gibbs sampler for Conjugate Bayesian Multivariate Linear Models
BPS_combine | Combine subset models wiht BPS
BPS_post | Perform the BPS sampling from posterior and posterior predictive given a set of stacking weights
BPS_postdraws | Compute the BPS posterior samples given a set of stacking weights
BPS_postdraws_MvT | Compute the BPS posterior samples given a set of stacking weights
BPS_post_MvT | Perform the BPS sampling from posterior and posterior predictive given a set of stacking weights
BPS_pred | Compute the BPS spatial prediction given a set of stacking weights
BPS_pred_MvT | Compute the BPS spatial prediction given a set of stacking weights
BPS_PseudoBMA | Combine subset models wiht Pseudo-BMA
BPS_weights | Compute the BPS weights by convex optimization
BPS_weights_MvT | Compute the BPS weights by convex optimization
conv_opt | Solver for Bayesian Predictive Stacking of Predictive densities convex optimization problem
CVXR_opt | Compute the BPS weights by convex optimization
dens_kcv | Compute the KCV of the density evaluations for fixed values of the hyperparameters
dens_kcv_MvT | Compute the KCV of the density evaluations for fixed values of the hyperparameters
dens_loocv | Compute the LOOCV 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
d_pred_cpp | Evaluate the density of a set of unobserved response with respect to the conditional posterior predictive
d_pred_cpp_MvT | Evaluate the density of a set of unobserved response with respect to the conditional posterior predictive
expand_grid_cpp | Build a grid from two vector (i.e. equivalent to 'expand.grid()' in 'R')
fit_cpp | Compute the parameters for the posteriors distribution of beta and Sigma (i.e. updated parameters)
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 | Return the CV predictive density evaluations for all the model combinations
models_dens_MvT | Return the CV predictive density evaluations for all the model combinations
post_draws | Sample R draws from the posterior distributions
post_draws_MvT | Sample R draws from the posterior distributions
pred_bayesMvLMconjugate | Predictive sampler for Conjugate Bayesian Multivariate Linear Models
r_pred_cond | Draw from the conditional posterior predictive for a set of unobserved covariates
r_pred_cond_MvT | Draw from the conditional posterior predictive for a set of unobserved covariates
r_pred_joint | Draw from the joint 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 | Draw from the marginals 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)
spPredict_BPS | Perform prediction for BPS accelerated models - loop over prediction set
subset_data | Function to subset data for meta-analysis