Maximum Likelihood Estimation for a Smooth Gaussian Random Field Model

DOI10.1137/15M105358XOpenAlexW2582155237MaRDI QIDQ5269857

Wanting Xu, Michael L. Stein

Publication date: 28 June 2017

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/15m105358x

zbMATH Keywords

cross validationcomputer experimentbest linear predictionsquared exponential covariance function

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Gaussian processes (60G15) Interpolation and approximation (educational aspects) (97N50)

Related Items (9)

Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes ⋮ Selection of a covariance function for a Gaussian random field aimed for modeling global optimization problems ⋮ Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolation ⋮ Small sample spaces for Gaussian processes ⋮ Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions ⋮ Gaussian Process-Based Dimension Reduction for Goal-Oriented Sequential Design ⋮ On the inference of applying Gaussian process modeling to a deterministic function ⋮ Probabilistic integration: a role in statistical computation? ⋮ Comment: unreasonable effectiveness of Monte Carlo

Uses Software

• Mathematica

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