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Extremes in random fieldsa theory an...

Yakir, Benjamin.

Extremes in random fieldsa theory and its applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Extremes in random fieldsBenjamin Yakir.
其他題名:	a theory and its applications /
作者:	Yakir, Benjamin.
出版者:	Chichester, West Sussex, United Kingdom :Wiley,2013.
面頁冊數:	1 online resource (xv, 236 p.) :ill.
附註:	Edition statement from running title area.
附註:	Machine generated contents note: Preface I Theory 1 Introduction 1.1 Distribution of extremes in random fields 1.2 Outline of the method 1.3 Gaussian and asymptotically Gaussian random fields 1.4 Applications 2 Basic Examples 2.1 Introduction 2.2 A power-one sequential test 2.3 A kernel-based scanning statistic 2.4 Other methods 3 Approximation of the Local Rate 3.1 Introduction 3.2 Preliminary localization and approximation 3.2.1 Localization 3.2.2 A discrete approximation 3.3 Measure transformation 3.4 Application of the localization theorem 3.5 Integration 4 From the Local to the Global 4.1 Introduction 4.2 Poisson approximation of probabilities 4.3 Average run length to false alarm 5 The Localization Theorem 5.1 Introduction 5.2 A simplifies version of the localization theorem 5.3 The Localization Theorem 5.4 A local limit theorem 5.5 Edge effects II Applications 6 Kolmogorov-Smirnov and Peacock 6.1 Introduction 6.2 Analysis of the one-dimensional case 6.3 Peacock's test 6.4 Relations to scanning statistics 7 Copy Number Variations 7.1 Introduction 7.2 The statistical model 7.3 Analysis of statistical properties 7.4 The False Discovery Rate (FDR) 8 Sequential Monitoring of an Image 8.1 Introduction 8.2 The statistical model 8.3 Analysis of statistical properties 8.4 Optimal change-point detection 9 Buffer Overflow 9.1 Introduction 9.2 The statistical model 9.3 Analysis of statistical properties 9.4 Long-range dependence and self-similarity 10 Computing Pickands' Constants 10.1 Introduction 10.2 Representations of constants 10.3 Analysis of statistical error 10.4 Local fluctuations Appendix A Mathematical Background A.1 Transforms A.2 Approximations of sum of independent random elements A.3 Concentration inequalities A.4 Random walks A.5 Renewal theory A.6 The Gaussian distribution A.7 Large sample inference A.8 Integration A.9 Poisson approximation A.10 Convexity References Index.
標題:	Random fields.
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9781118720608
ISBN:	9781118720615 (electronic bk.)

Extremes in random fieldsa theory and its applications /
Yakir, Benjamin.

Extremes in random fieldsa theory and its applications /[electronic resource] :Benjamin Yakir. - 1st ed. - Chichester, West Sussex, United Kingdom :Wiley,2013. - 1 online resource (xv, 236 p.) :ill. - Wiley series in probability and statistics. - Wiley series in probability and statistics..

Edition statement from running title area.

Includes bibliographical references (p. 221-222) and index.

"Reading chapters of the book can be used as a primer for a student who is then required to analyze a new problem that was not digested for him/her in the book"--

ISBN: 9781118720615 (electronic bk.)

LCCN: 2013025343Subjects--Topical Terms:

186303
Random fields.

LC Class. No.: QA274.45

Dewey Class. No.: 519.2/3

Extremes in random fieldsa theory and its applications /
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245 1 0 $a Extremes in random fields $h [electronic resource] : $b a theory and its applications / $c Benjamin Yakir.
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260 $a Chichester, West Sussex, United Kingdom : $b Wiley, $c 2013.
300 $a 1 online resource (xv, 236 p.) : $b ill.
490 1 $a Wiley series in probability and statistics
500 $a Edition statement from running title area.
500 $a Machine generated contents note: Preface I Theory 1 Introduction 1.1 Distribution of extremes in random fields 1.2 Outline of the method 1.3 Gaussian and asymptotically Gaussian random fields 1.4 Applications 2 Basic Examples 2.1 Introduction 2.2 A power-one sequential test 2.3 A kernel-based scanning statistic 2.4 Other methods 3 Approximation of the Local Rate 3.1 Introduction 3.2 Preliminary localization and approximation 3.2.1 Localization 3.2.2 A discrete approximation 3.3 Measure transformation 3.4 Application of the localization theorem 3.5 Integration 4 From the Local to the Global 4.1 Introduction 4.2 Poisson approximation of probabilities 4.3 Average run length to false alarm 5 The Localization Theorem 5.1 Introduction 5.2 A simplifies version of the localization theorem 5.3 The Localization Theorem 5.4 A local limit theorem 5.5 Edge effects II Applications 6 Kolmogorov-Smirnov and Peacock 6.1 Introduction 6.2 Analysis of the one-dimensional case 6.3 Peacock's test 6.4 Relations to scanning statistics 7 Copy Number Variations 7.1 Introduction 7.2 The statistical model 7.3 Analysis of statistical properties 7.4 The False Discovery Rate (FDR) 8 Sequential Monitoring of an Image 8.1 Introduction 8.2 The statistical model 8.3 Analysis of statistical properties 8.4 Optimal change-point detection 9 Buffer Overflow 9.1 Introduction 9.2 The statistical model 9.3 Analysis of statistical properties 9.4 Long-range dependence and self-similarity 10 Computing Pickands' Constants 10.1 Introduction 10.2 Representations of constants 10.3 Analysis of statistical error 10.4 Local fluctuations Appendix A Mathematical Background A.1 Transforms A.2 Approximations of sum of independent random elements A.3 Concentration inequalities A.4 Random walks A.5 Renewal theory A.6 The Gaussian distribution A.7 Large sample inference A.8 Integration A.9 Poisson approximation A.10 Convexity References Index.
504 $a Includes bibliographical references (p. 221-222) and index.
520 $a "Reading chapters of the book can be used as a primer for a student who is then required to analyze a new problem that was not digested for him/her in the book"-- $c Provided by publisher.
588 $a Description based on online resource; title from PDF title page (Wiley, viewed September 17, 2013)
650 0 $a Random fields. $3 186303
830 0 $a Wiley series in probability and statistics. $3 324851
856 4 0 $u http://onlinelibrary.wiley.com/book/10.1002/9781118720608