Optimal Model Average Prediction in Orthogonal Kriging Models

被引：3

作者：

Wang, Jun ^{[1
]}

He, Jiabei ^{[1
]}

Liang, Hua ^{[2
]}

Li, Xinmin ^{[1
]}

机构：

[1] Qingdao Univ, Sch Math & Stat, Qingdao 266071, Peoples R China

[2] George Washington Univ, Dept Stat, Washington, DC 20052 USA

来源：

JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY | 2024年 / 37卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Asymptotic optimality; Mallows criterion; optimal model averaging; orthogonal kriging model; VARIABLE SELECTION; GENERALIZED-METHOD;

D O I：

10.1007/s11424-024-2333-y

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The main objective of this paper is to consider model averaging methods for kriging models. This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square error. Simulation studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its superiority. The authors also analyse a real dataset for an illustration.

引用

页码：1080 / 1099

页数：20

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