A Bayesian Analysis of Kriging

Publisher Website
Google Scholar
Abstract
This article is concerned with predicting for Gaussian random fields in a way that appropriately deals with uncertainty in the covariance function. To this end, we analyze the best linear unbiased prediction procedure within a Bayesian framework. Particular attention is paid to the treatment of parameters in the covariance structure and their effect on the quality, both real and perceived, of the prediction. These ideas are implemented using topographical data from Davis.

This publication has 0 references indexed in Scilit: