BPS_weights_MvT: Compute the BPS weights by convex optimization

In spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

Compute the BPS weights by convex optimization

Description

Compute the BPS weights by convex optimization

Usage

BPS_weights_MvT(data, priors, coords, hyperpar, K)

Arguments

data	list two elements: first named Y, second named X
priors	list priors: named \mu_B,V_r,\Psi,\nu
coords	matrix sample coordinates for X and Y
hyperpar	list two elemets: first named \alpha, second named \phi
K	integer number of folds

Value

matrix posterior predictive density evaluations (each columns represent a different model)

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