BPS_post_MvT: Perform the BPS sampling from posterior and posterior...

In spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

Perform the BPS sampling from posterior and posterior predictive given a set of stacking weights

Description

Perform the BPS sampling from posterior and posterior predictive given a set of stacking weights

Usage

BPS_post_MvT(data, X_u, priors, coords, crd_u, hyperpar, W, R)

Arguments

data	list two elements: first named Y, second named X
X_u	matrix unobserved instances covariate matrix
priors	list priors: named \mu_B,V_r,\Psi,\nu
coords	matrix sample coordinates for X and Y
crd_u	matrix unboserved instances coordinates
hyperpar	list two elemets: first named \alpha, second named \phi
W	matrix set of stacking weights
R	integer number of desired samples

Value

list BPS posterior predictive samples

spBPS documentation built on March 19, 2026, 5:07 p.m.