r_pred_cond_MvT: Draw from the conditional posterior predictive for a set of...

In spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

Draw from the conditional posterior predictive for a set of unobserved covariates

Description

Draw from the conditional posterior predictive for a set of unobserved covariates

Usage

r_pred_cond_MvT(data, X_u, d_u, d_us, hyperpar, poster, post)

Arguments

data	list two elements: first named Y, second named X
X_u	matrix unobserved instances covariate 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 \alpha, second named \phi
poster	list output from fit_cpp_MvT function
post	list output from post_draws_MvT function

Value

list posterior predictive samples

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