Extremes in random fields: a theory and its applications
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Chichester, West Sussex, U.K.
John Wiley & Sons Inc.
2013
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| Schlagworte: | |
| Beschreibung: | Includes bibliographical references 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"-- |
| Beschreibung: | xiii, 225 p. |
| ISBN: | 9781118720615 |
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| 100 | 1 | |a Yakir, Benjamin |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Extremes in random fields |b a theory and its applications |c Benjamin Yakir |
| 264 | 1 | |a Chichester, West Sussex, U.K. |b John Wiley & Sons Inc. |c 2013 | |
| 300 | |a xiii, 225 p. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 500 | |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"-- | ||
| 505 | 0 | |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 | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-029584743 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Datensatz im Suchindex
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| author | Yakir, Benjamin |
| author_facet | Yakir, Benjamin |
| author_role | aut |
| author_sort | Yakir, Benjamin |
| author_variant | b y by |
| building | Verbundindex |
| bvnumber | BV044177898 |
| classification_rvk | SK 820 |
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| contents | 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 |
| ctrlnum | (ZDB-30-PAD)EBC1434101 (ZDB-89-EBL)EBL1434101 (OCoLC)862047261 (DE-599)BVBBV044177898 |
| dewey-full | 519.2/3 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.2/3 |
| dewey-search | 519.2/3 |
| dewey-sort | 3519.2 13 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| indexdate | 2024-07-10T07:45:53Z |
| institution | BVB |
| isbn | 9781118720615 |
| language | English |
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| physical | xiii, 225 p. |
| psigel | ZDB-30-PAD |
| publishDate | 2013 |
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| publisher | John Wiley & Sons Inc. |
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| spelling | Yakir, Benjamin Verfasser aut Extremes in random fields a theory and its applications Benjamin Yakir Chichester, West Sussex, U.K. John Wiley & Sons Inc. 2013 xiii, 225 p. txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references 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"-- 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 Random fields Extremwert (DE-588)4137272-4 gnd rswk-swf Zufälliges Feld (DE-588)4191094-1 gnd rswk-swf Zufälliges Feld (DE-588)4191094-1 s Extremwert (DE-588)4137272-4 s 1\p DE-604 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-118-62020-5 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Yakir, Benjamin Extremes in random fields a theory and its applications 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 Random fields Extremwert (DE-588)4137272-4 gnd Zufälliges Feld (DE-588)4191094-1 gnd |
| subject_GND | (DE-588)4137272-4 (DE-588)4191094-1 |
| title | Extremes in random fields a theory and its applications |
| title_auth | Extremes in random fields a theory and its applications |
| title_exact_search | Extremes in random fields a theory and its applications |
| title_full | Extremes in random fields a theory and its applications Benjamin Yakir |
| title_fullStr | Extremes in random fields a theory and its applications Benjamin Yakir |
| title_full_unstemmed | Extremes in random fields a theory and its applications Benjamin Yakir |
| title_short | Extremes in random fields |
| title_sort | extremes in random fields a theory and its applications |
| title_sub | a theory and its applications |
| topic | Random fields Extremwert (DE-588)4137272-4 gnd Zufälliges Feld (DE-588)4191094-1 gnd |
| topic_facet | Random fields Extremwert Zufälliges Feld |
| work_keys_str_mv | AT yakirbenjamin extremesinrandomfieldsatheoryanditsapplications |