FIXED-DOMAIN ASYMPTOTICS UNDER VECCHIA'S APPROXIMATION OF SPATIAL PROCESS LIKELIHOODS

被引：1

作者：

Zhang, Lu ^{[1
]}

Tang, Wenpin ^{[2
]}

Banerjee, Sudipto ^{[3
]}

机构：

[1] Univ Southern Calif, Dept Populat & Publ Hlth Sci, Div Biostat, Los Angeles, CA 90089 USA

[2] Columbia Univ, Dept Ind Engn & Operat Res, New York, NY 10027 USA

[3] Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA 90095 USA

来源：

STATISTICA SINICA | 2024年 / 34卷 / 04期

关键词：

Fixed-domain asymptotics; Gaussian processes; Matern covariance function; microergodic parameters; spatial statistics; GAUSSIAN PROCESS MODELS; LINEAR PREDICTIONS;

D O I：

10.5705/ss.202021.0428

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Statistical modeling for massive spatial data sets has generated a substantial body of literature on scalable spatial processes based on Vecchia'sapproximation.Vecchia's approximation for Gaussian process models enablesfast evaluation of the likelihood by restricting dependencies at a location to itsneighbors. We establish inferential properties of microergodic spatial covarianceparameters within the paradigm of fixed-domain asymptotics when the parametersare estimated using Vecchia's approximation. We explore the conditions requiredto formally establish these properties, theoretically and empirically. Our resultsfurther corroborate the effectiveness of Vecchia's approximation from the standpoint of fixed-domain asymptotics

引用

页码：1863 / 1881

页数：19

共 28 条

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