Statistical Estimation for Truncated Exponential Families -  Masafumi Akahira

Statistical Estimation for Truncated Exponential Families (eBook)

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2017 | 1st ed. 2017
XI, 122 Seiten
Springer Singapore (Verlag)
978-981-10-5296-5 (ISBN)
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This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping readers understand the meaning and implications of both regularity and irregularity through a certain family of distributions. In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This focus includes the (truncated) Pareto distribution, which is widely used in various fields such as finance, physics, hydrology, geology, astronomy, and other disciplines. The family is essential in that it links both regular and nonregular distributions, as it becomes a regular exponential family if the truncation parameter is known. The emphasis is on presenting new results on the maximum likelihood estimation of a natural parameter or truncation parameter if one of them is a nuisance parameter. In order to obtain more information on the truncation, the Bayesian approach is also considered. Further, the application to some useful truncated distributions is discussed. The illustrated clarification of the nonregular structure provides researchers and practitioners with a solid basis for further research and applications.



Masafumi Akahira, Professor Emeritus, Institute of Mathematics, University of Tsukuba 

This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping readers understand the meaning and implications of both regularity and irregularity through a certain family of distributions. In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This focus includes the (truncated) Pareto distribution, which is widely used in various fields such as finance, physics, hydrology, geology, astronomy, and other disciplines. The family is essential in that it links both regular and nonregular distributions, as it becomes a regular exponential family if the truncation parameter is known. The emphasis is on presenting new results on the maximum likelihood estimation of a natural parameter or truncation parameter if one of them is a nuisance parameter. In order to obtain more information on the truncation, the Bayesian approach is also considered. Further, the application to some useful truncated distributions is discussed. The illustrated clarification of the nonregular structure provides researchers and practitioners with a solid basis for further research and applications.

Masafumi Akahira, Professor Emeritus, Institute of Mathematics, University of Tsukuba 

Chapter I: One-sided truncated exponential family of distributions.- Chapter II: Two-sided truncated exponential family of distributions.

Erscheint lt. Verlag 26.7.2017
Reihe/Serie JSS Research Series in Statistics
JSS Research Series in Statistics
JSS Research Series in Statistics
SpringerBriefs in Statistics
SpringerBriefs in Statistics
Zusatzinfo XI, 122 p. 10 illus.
Verlagsort Singapore
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Mathematik / Informatik Mathematik Computerprogramme / Computeralgebra
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Wirtschaft
Schlagworte Maximum Likelihood Estimator • Natural Parameter • Second Order Asymptotic Loss • Truncated Exponential Family • Truncation Parameter
ISBN-10 981-10-5296-4 / 9811052964
ISBN-13 978-981-10-5296-5 / 9789811052965
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