d_pred_cpp: Evaluate the density of a set of unobserved response with...

In spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

Evaluate the density of a set of unobserved response with respect to the conditional posterior predictive

Description

Evaluate the density of a set of unobserved response with respect to the conditional posterior predictive

Usage

d_pred_cpp(data, X_u, Y_u, d_u, d_us, hyperpar, poster)

Arguments

data	list two elements: first named Y, second named X
X_u	matrix unobserved instances covariate matrix
Y_u	matrix unobserved instances response matrix
d_u	matrix unobserved instances distance matrix
d_us	matrix cross-distance between unobserved and observed instances matrix
hyperpar	list two elemets: first named \delta, second named \phi
poster	list output from fit_cpp function

Value

vector posterior predictive density evaluations

spBPS documentation built on Oct. 25, 2024, 5:07 p.m.