文章基本信息

标题：Optimal Block Size for Variance Estimation by a Spatial Block Bootstrap Method
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作者：Daniel J. Nordman ; Soumendra N. Lahiri ; Iowa State University, Ames 等
期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2007
卷号：69
期号：03
出版社：Indian Statistical Institute
摘要：This paper considers the block selection problem for a block bootstrap variance estimator applied to spatial data on a regular grid. We develop precise formulae for the optimal block sizes that minimize the mean squared error of the bootstrap variance estimator. We then describe practical methods for estimating these spatial block sizes and prove the consistency of a block selection method by Hall, Horowitz and Jing (1995), originally introduced for time series. The spatial block bootstrap method is illustrated through data examples, and its performance is investigated through several simulation studies.
关键词：Block bootstrap, empirical block choice, stationary random fields.