Sinossi
This important book in statistical theory by one of the leading experts in this area unifies the two two important approaches to statistical parameter estimation. It will be of interest to researchers and graduate students in both mathematical statistics and probability theory.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
The General Framework.- An Alternative Approach: E-Sufficiency.- Asymptotic Confidence Zones of Minimum Size.- Asymptotic Quasi-Likelihood.- Combining Estimating Functions.- Projected Quasi-Likelihood.- Bypassing the Likelihood.- Hypothesis Testing.- Infinite Dimensional Problems.- Miscellaneous Applications.- Consistency and Asymptotic Normality for Estimating Functions.- Complements and Strategies for Application.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter Estimation (Springer Series in Statistics)
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Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter Estimation (Springer Series in Statistics)
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Quasi-Likelihood And Its Application
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Springer New York Mrz 2013, 2013
ISBN 10: 1475771045
ISBN 13: 9781475771046
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The first account in book form of all the essential features of the quasi-likelihood methodology, stressing its value as a general purpose inferential tool. The treatment is rather informal, emphasizing essential principles rather than detailed proofs, and readers are assumed to have a firm grounding in probability and statistics at the graduate level. Many examples of the use of the methods in both classical statistical and stochastic process contexts are provided. 252 pp. Englisch. Codice articolo 9781475771046
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Quasi-Likelihood And Its Application
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first account in book formThe author is one of the leading experts in this areaThe first account in book form of all the essential features of the quasi-likelihood methodology, stressing its value as a general purpose inferential tool. The treat. Codice articolo 4207696
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Quasi-likelihood and Its Application: A General Approach to Optimal Parameter Estimation
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Paperback. Condizione: Brand New. 246 pages. 9.25x6.10x0.57 inches. In Stock. Codice articolo x-1475771045
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Quasi-Likelihood And Its Application | A General Approach to Optimal Parameter Estimation
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Taschenbuch. Condizione: Neu. Quasi-Likelihood And Its Application | A General Approach to Optimal Parameter Estimation | Christopher C. Heyde | Taschenbuch | x | Englisch | 2013 | Springer | EAN 9781475771046 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 105651767
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Quasi-Likelihood And Its Application
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Springer, Springer Mär 2013, 2013
ISBN 10: 1475771045
ISBN 13: 9781475771046
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is concerned with the general theory of optimal estimation of - rameters in systems subject to random e ects and with the application of this theory. The focus is on choice of families of estimating functions, rather than the estimators derived therefrom, and on optimization within these families. Only assumptions about means and covariances are required for an initial d- cussion. Nevertheless, the theory that is developed mimics that of maximum likelihood, at least to the rst order of asymptotics. The term quasi-likelihood has often had a narrow interpretation, asso- ated with its application to generalized linear model type contexts, while that of optimal estimating functions has embraced a broader concept. There is, however, no essential distinction between the underlying ideas and the term quasi-likelihood has herein been adopted as the general label. This emphasizes its role in extension of likelihood based theory. The idea throughout involves nding quasi-scores from families of estimating functions. Then, the qua- likelihood estimator is derived from the quasi-score by equating to zero and solving, just as the maximum likelihood estimator is derived from the like- hood score.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch. Codice articolo 9781475771046
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Quasi-Likelihood And Its Application : A General Approach to Optimal Parameter Estimation
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is concerned with the general theory of optimal estimation of - rameters in systems subject to random e ects and with the application of this theory. The focus is on choice of families of estimating functions, rather than the estimators derived therefrom, and on optimization within these families. Only assumptions about means and covariances are required for an initial d- cussion. Nevertheless, the theory that is developed mimics that of maximum likelihood, at least to the rst order of asymptotics. The term quasi-likelihood has often had a narrow interpretation, asso- ated with its application to generalized linear model type contexts, while that of optimal estimating functions has embraced a broader concept. There is, however, no essential distinction between the underlying ideas and the term quasi-likelihood has herein been adopted as the general label. This emphasizes its role in extension of likelihood based theory. The idea throughout involves nding quasi-scores from families of estimating functions. Then, the qua- likelihood estimator is derived from the quasi-score by equating to zero and solving, just as the maximum likelihood estimator is derived from the like- hood score. Codice articolo 9781475771046
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Quasi-Likelihood And Its Application: A General Approach to Optimal Parameter Estimation (Springer Series in Statistics)
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