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International Journal for Uncertainty Quantification
IF: 3.259 5-Year IF: 2.547 SJR: 0.531 SNIP: 0.8 CiteScore™: 1.52

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027823
Forthcoming Article

PIG Process: Joint Modeling of Point and Integral Responses in Computer Experiments

Heng Su
Wells Fargo Bank
Rui Tuo
Texas A&M University
Jeff Wu
Georgia Institute of Technology


Motivated by work on building energy simulation, this paper develops a new class of models called point-integral Gaussian (PIG) processes. The covariance structures of these models are obtained and their parameter estimation and prediction are derived. In the case of axis-parallel rectangular regions, closed form expressions for the covariance functions are obtained. Two simulated examples are used to demonstrate the use of the PIG process models and show their superior performance over those without the integral information.