Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

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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