On asymptotic distribution and asymptotic efficiency of least squares estimators of spatial variogram parameters

被引:52
|
作者
Lahiri, SN
Lee, YD
Cressie, N
机构
[1] Iowa State Univ, Dept Stat, Ames, IA 50011 USA
[2] Ohio State Univ, Dept Stat, Columbus, OH 43210 USA
基金
美国国家科学基金会;
关键词
asymptotic efficiency; infill sampling; spatial processes; variogram; weighted least squares estimators;
D O I
10.1016/S0378-3758(01)00198-7
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
In this article, we consider the least-squares approach for estimating parameters of a spatial variograin and establish consistency and asymptotic normality of these estimators under general conditions. Large-sample distributions are also established under a spatial regression model where the sampling design possibly has an infill sampling component. These results allow us to investigate efficiencies of different least squares variogram-parameter estimators in large samples, We provide two necessary and sufficient conditions for these estimators to be asymptotically efficient, It is an interesting consequence of our results that when the number of lags used to define the estimators is chosen to be equal to the number of variogram parameters to be estimated, the ordinary least squares estimator, the weighted least squares and the generalized least squares estimators are all asymptotically efficient. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
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页码:65 / 85
页数:21
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