Practically Applicable Central Limit Theorem for Spatial Statistics
  • Park, Byeong U.
  • Kim, Tae Yoon
  • Park, Jeong-Soo
  • Hwang, S. Y.
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10
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9

초록

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.

키워드

Central limit theoremNearly infill domain samplingDensity estimationLONG-RANGE DEPENDENCEDENSITY-ESTIMATIONRANDOM-FIELDSESTIMATORS
제목
Practically Applicable Central Limit Theorem for Spatial Statistics
저자
Park, Byeong U.Kim, Tae YoonPark, Jeong-SooHwang, S. Y.
DOI
10.1007/s11004-008-9184-2
발행일
2009-07
유형
Article
저널명
Mathematical Geosciences
41
5
페이지
555 ~ 569