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The stress-strength model and its generalizations : theory and applications / Samuel Kotz, Yan Lumelskii, Marianna Pensky.

By: Kotz, SamuelContributor(s): Lumelʹskiĭ, I︠A︡n Petrovich | Pensky, MariannaMaterial type: TextTextPublication details: River Edge, NJ : World Scientific, ©2003. Description: 1 online resource (xvii, 253 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9812564519; 9789812564511; 1281876895; 9781281876898; 9789812380579; 9812380574Subject(s): Reliability (Engineering) -- Statistical methods | Estimation theory | Distribution (Probability theory) | Mathematical statistics | TECHNOLOGY & ENGINEERING -- Quality Control | Reliability (Engineering) -- Statistical methods | Estimation theory | Distribution (Probability theory) | Mathematical statistics | Distribution (Probability theory) | Estimation theory | Mathematical statistics | Reliability (Engineering) -- Statistical methodsGenre/Form: Electronic book. | Electronic books. Additional physical formats: Print version:: Stress-strength model and its generalizations.DDC classification: 620/.00452/0727 LOC classification: TA169 | .K674 2003ebOther classification: B845. 9 | O346. 2 Online resources: Click here to access online
Contents:
Preface; Some Notations and Abbreviations; Contents; Chapter 1 The Stress-Strength Models. Mathematics, History, and Applications; Chapter 2 The Theory and Some Useful Approaches; Chapter 3 Parametric Point Estimation; Chapter 4 Parametric Statistical Inference; Chapter 5 Nonparametric Models; Chapter 6 Some Selected Special Cases; Chapter 7 Applications and Examples; Bibliography; Index.
Summary: This important book presents developments in a remarkable field of inquiry in statistical/probability theory - the stress-strength model. Many papers in the field include the enigmatic "words" P(X<Y) - or something similar - in the title. This reflects the long-established concept of ordering of distributions. The basic impetus for the study carried out by the authors of this book is the general concept of stress-strength as an interpretation of the P(X<Y) relationships, which leads to applications in reliability engineering, economics and modern medicine. The Stress-Strength Model and Its Generalizations collects and digests theoretical and practical results on the theory and applications of the stress-strength relationships in industrial and economic systems - results that have been scattered in the literature during the last 40-odd years - and augments and presents them for the first time in a unified manner suitable for practitioners as well as probabilists and theoretical and applied statisticians.
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"P(X<Y)."

Includes bibliographical references (pages 233-249) and index.

Print version record.

Preface; Some Notations and Abbreviations; Contents; Chapter 1 The Stress-Strength Models. Mathematics, History, and Applications; Chapter 2 The Theory and Some Useful Approaches; Chapter 3 Parametric Point Estimation; Chapter 4 Parametric Statistical Inference; Chapter 5 Nonparametric Models; Chapter 6 Some Selected Special Cases; Chapter 7 Applications and Examples; Bibliography; Index.

This important book presents developments in a remarkable field of inquiry in statistical/probability theory - the stress-strength model. Many papers in the field include the enigmatic "words" P(X<Y) - or something similar - in the title. This reflects the long-established concept of ordering of distributions. The basic impetus for the study carried out by the authors of this book is the general concept of stress-strength as an interpretation of the P(X<Y) relationships, which leads to applications in reliability engineering, economics and modern medicine. The Stress-Strength Model and Its Generalizations collects and digests theoretical and practical results on the theory and applications of the stress-strength relationships in industrial and economic systems - results that have been scattered in the literature during the last 40-odd years - and augments and presents them for the first time in a unified manner suitable for practitioners as well as probabilists and theoretical and applied statisticians.

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