R: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

# Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

## Documentation for package ‘spBPS’ version 2.0-1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## 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_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_MvT | Compute the BPS spatial prediction given a set of stacking weights
BPS_PseudoBMA | Combine subset models wiht Pseudo-BMA
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_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
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_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
predict.spBPS | Predict at new locations using a fitted spBPS model
pred_bayesMvLMconjugate | Predictive sampler for Conjugate Bayesian Multivariate Linear Models
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