The Inverse Gaussian Distribution: A Case Study in Exponential Families - Rilegato

Seshadri, V.

Rilegato

ISBN 10: 0198522436 ISBN 13: 9780198522430

Casa editrice: Clarendon Press, 1994

Riassunto

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 an important special case.

Chapter 2 concerns the basic theory of exponential functions, focusing on the inverse Gaussian Law. Chapter 3 is devoted to various characterization results, 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 and interference are provided. Research workers will find inspiration for further investigations.

Su questo libro

Recensione:

This book is an important addition to the literature on the inverse Gaussian distribution. (J.L. Folks, Oklahoma State University, International Statistical Institute, Vol. 14, No. 3 - December 1994)

Contenuti:

• 1.: A historical survey
• 2.: Properties of the inverse Gaussian distribution
• 3.: Characterizations
• 4.: Combinations
• 5.: Inverse natural exponential families on R
• 6.: Statistical properties
• References
• Author index
• Subject index

Su questa edizione

• Editore: Clarendon Press
• Data di pubblicazione: 1994
• ISBN 10: 0198522436
• ISBN 13: 9780198522430
• Rilegatura: Copertina rigida
• Numero di pagine: 268