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International Journal for Uncertainty Quantification
Fator do impacto: 4.911 FI de cinco anos: 3.179 SJR: 1.008 SNIP: 0.983 CiteScore™: 5.2

ISSN Imprimir: 2152-5080
ISSN On-line: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2019027823
pages 331-349

PIG PROCESS: JOINT MODELING OF POINT AND INTEGRAL RESPONSES IN COMPUTER EXPERIMENTS

Heng Su
Wells Fargo Bank, Charlotte, NC 28202, USA
Rui Tuo
Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX 77843, USA
C. F. Jeff Wu
The H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

RESUMO

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.

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