Tail approximations for maxima of random fields by likelihood ratio transformations

D. Siegmund; B. Yakir; N. Zhang

doi:10.1080/07474946.2010.487428

Tail approximations for maxima of random fields by likelihood ratio transformations

D. Siegmund^*, B. Yakir, N. Zhang

^*Corresponding author for this work

Department of Statistics

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

The likelihood ratio method for dealing with change-point problems of Yakir and Pollak (1998), which has subsequently been extended to deal with a wide variety of problems involving maxima of random fields, has as a key ingredient a conditional local limit theorem for a log-likelihood ratio, given an almost independent "local" sigma-algebra. This article contains a general version of that theorem, illustrated by several examples.

Original language	English
Pages (from-to)	245-262
Number of pages	18
Journal	Sequential Analysis
Volume	29
Issue number	3
DOIs	https://doi.org/10.1080/07474946.2010.487428
State	Published - 2010

Bibliographical note

Funding Information:
This research has been supported by the US National Science Foundation and by the Israel–US Binational Science Foundation Grant 2006101.

Keywords

Change of measure
Change-point
Likelihood ratio
Local limit theorem

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10.1080/07474946.2010.487428

Cite this

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Tail approximations for maxima of random fields by likelihood ratio transformations

Abstract

Bibliographical note

Keywords

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