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The Inverse Gaussian Distribution: A Case Study in Exponential Families (Oxford Science Publications) - Hardcover

 
9780198522430: The Inverse Gaussian Distribution: A Case Study in Exponential Families (Oxford Science Publications)
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This book provides a comprehensive and penetrating account of the inverse Gaussian law. Beginning with an exhaustive historical overview that presents--for the first time--Etienne Halphen's pioneering wartime contributions, the book proceeds to a rigorous exposition of the theory of exponential families, focusing in particular on the inverse Gaussian law. The book also considers inverse natural exponential families and provides a detailed analysis of the "Tweedie" scale. A wealth of properties, characterization, new concepts of inverse exponential families, useful expositions of statistical results, and an updated list of about 400 key references are included as well. The book will be welcomed by students and researchers of statistics and probability.

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About the Author:
V. Seshadri is at McGill University.
Review:

"This text provides a thorough, predominantly theoretical, overview of the inverse gaussian distribution and should prove indispensable to those who have discovered the value of this distribution in quality and reliability engineering applications." -- Journal of Quality Technology


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  • PublisherClarendon Press
  • Publication date1994
  • ISBN 10 0198522436
  • ISBN 13 9780198522430
  • BindingHardcover
  • Edition number1
  • Number of pages272

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Book Description Hardcover. Condition: new. Hardcover. This book begins with a historical survey of `generalized inverse Gaussian laws', in which the wartime contribution of Etienne Halphen is presented for the first time. The inverse Gaussian distribution, its properties, and its implications are set in a wide perspective. The concepts of inversion and inverse natural exponential functions are presented, together with an analysis of the `Tweedie' scale, of which the Gaussian distribution is animportant special case. Chapter 2 concerns the basic theory of exponential functions, focusing on the inverse Gaussian Law. Chapter 3 is devoted to various characterizationresults, while Chapter 4 is concerned with the construction of multivariate distributions, and the relationship to simplex distributions, combinations, and finite mixtures. Chapter 5 introduces the concept of inverse natural exponential functions and Chapter 6 presents useful statistical results. Up-to-date research is presented in the form of exercises, a special chapter on characterizations is included, and a summary of statistical issues concerning estimation andinterference are provided. Research workers will find inspiration for further investigations. Beginning with a historical survey, the book provides a comprehensive overview of natural exponential families, with emphasis on the inverse Gaussian Law. Included are a range of properties, characterizations, new concepts of inverse exponential families, useful expositions of statistical results, and an updated list of approximately 400 references. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780198522430

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Book Description Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a comprehensive and penetrating account of the inverse Gaussian law. Beginning with an exhaustive historical overview that presents--for the first time--Etienne Halphen's pioneering wartime contributions, the book proceeds to a rigorous exposition of the theory of exponential families, focusing in particular on the inverse Gaussian law. The book also considers inverse natural exponential families and provides a detailed analysis of the 'Tweedie' scale. A wealth of properties, characterization, new concepts of inverse exponential families, useful expositions of statistical results, and an updated list of about 400 key references are included as well. The book will be welcomed by students and researchers of statistics and probability. Seller Inventory # 9780198522430

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