Practically Applicable Central Limit Theorem for Spatial Statistics

被引：10

作者：

Park, Byeong U. ^{[2
]}

Kim, Tae Yoon ^{[1
]}

Park, Jeong-Soo ^{[3
]}

Hwang, S. Y. ^{[4
]}

机构：

[1] Keimyung Univ, Dept Stat, Taegu, South Korea

[2] Seoul Natl Univ, Dept Stat, Seoul, South Korea

[3] Chonnam Natl Univ, Dept Stat, Kwangju, South Korea

[4] Sookmyung Womens Univ, Dept Stat, Seoul, South Korea

来源：

MATHEMATICAL GEOSCIENCES | 2009年 / 41卷 / 05期

关键词：

Central limit theorem; Nearly infill domain sampling; Density estimation; DENSITY-ESTIMATION; ESTIMATORS;

D O I：

10.1007/s11004-008-9184-2

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Let {Z(s):saDaS dagger a"e (d) } be a zero mean stationary random field observed at a finite number of locations. Lahiri (Sankhya Ser. A 65:356-388, 2003) proved spatial central limit theorems (CLT) for a (i=1) (n) Z(s (i) ) assuming a 'nearly infill domain sampling'. Applications of his results depended on the underlying spatial sampling region and the design in a complicated fashion. The main objective of this paper is to provide CLTs that could be applied easily in practice. We present two main results assuming a 'nearly infill domain sampling' defined mainly in terms of dependence. Theorem 1 establishes a CLT for a (i=1) (n) Z(s (i) ) and Theorem 2 is obtained mainly for applications to density estimates. We report on a simulation study for illustrating a way of applying our results in practice.

引用

页码：555 / 569

页数：15

共 18 条

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