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Statistical Estimation for Truncated Exponential Families
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Catalogue Information
Nome campo
dettagli
Dewey Class
519.5
Titolo
Statistical Estimation for Truncated Exponential Families ([EBook]) / by Masafumi Akahira.
Autore
Akahira, Masafumi
Other name(s)
SpringerLink (Online service)
Pubblicazione
Singapore : : Springer Singapore : : Imprint: Springer, , 2017.
Physical Details
XI, 122 p. 10 illus. : online resource.
Serie
SpringerBriefs in Statistics
2191-544X
ISBN
9789811052965
Summary Note
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.:
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-981-10-5296-5
Link alle Opere Legate
Riferimenti soggetto:
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Statistical Theory and Methods
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Statistics
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Statistics and Computing/Statistics Programs
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Statistics for Business/Economics/Mathematical Finance/Insurance
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Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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Authors:
Akahira, Masafumi
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Corporate Authors:
SpringerLink (Online service)
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Series:
SpringerBriefs in Statistics
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Classification:
519.5
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