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June 2000 Estimating structured correlation matrices in smooth Gaussian random field models
Tao-Kai Lam, Wei-Liem Loh
Ann. Statist. 28(3): 880-904 (June 2000). DOI: 10.1214/aos/1015952003

Abstract

This article considers the estimation of structured correlation matrices in infinitely differentiable Gaussian random field models.The problem is essentially motivated by the stochastic modeling of smooth deterministic responses in computer experiments.In particular, the log-likelihood function is determined explicitly in closed-form and the sieve maximum likelihood estimators are shown to be strongly consistent under mild conditions.

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Tao-Kai Lam. Wei-Liem Loh. "Estimating structured correlation matrices in smooth Gaussian random field models." Ann. Statist. 28 (3) 880 - 904, June 2000. https://doi.org/10.1214/aos/1015952003

Information

Published: June 2000
First available in Project Euclid: 12 March 2002

zbMATH: 1105.62376
MathSciNet: MR1792792
Digital Object Identifier: 10.1214/aos/1015952003

Subjects:
Primary: 62D05
Secondary: 62E20 , 62G15

Keywords: computer experiment , sieve maximum likelihood estimation , smooth Gaussian random field , strong consistency , structured correlation matrix

Rights: Copyright © 2000 Institute of Mathematical Statistics

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Vol.28 • No. 3 • June 2000
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