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1. |
Record Nr. |
UNINA9910273520803321 |
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Titolo |
Bookmarks |
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Pubbl/distr/stampa |
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San Mateo, CA, : Phillips & Nelson Media, 2002- |
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Berkeley, CA, : Bookmarks Publishing, LLC |
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ISSN |
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Descrizione fisica |
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volumes : illustration (some col.), ports. ; ; 28 cm |
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Disciplina |
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Soggetti |
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Books |
Books - United States |
Books and reading |
Books and reading - United States |
Periodicals. |
Reviews. |
United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Periodico |
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Note generali |
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"For everyone who hasn't read everything." |
Title from cover. |
Published: Mill Valley, Calif., 2003- |
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2. |
Record Nr. |
UNINA9910254274903321 |
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Autore |
Akahira Masafumi |
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Titolo |
Statistical Estimation for Truncated Exponential Families / / by Masafumi Akahira |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2017 |
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ISBN |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (XI, 122 p. 10 illus.) |
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Collana |
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JSS Research Series in Statistics, , 2364-0065 |
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Disciplina |
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Soggetti |
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Statistics |
Mathematical statistics - Data processing |
Statistical Theory and Methods |
Statistics and Computing |
Statistics in Business, Management, Economics, Finance, Insurance |
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Sommario/riassunto |
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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 |
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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. |
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