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

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