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Inference in Hidden Markov Models, Olivier Capp?; Eric Moulines; Tobias Ryden


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Цена: 27251.00р.
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Автор: Olivier Capp?; Eric Moulines; Tobias Ryden
Название:  Inference in Hidden Markov Models
ISBN: 9781441923196
Издательство: Springer
Классификация:







ISBN-10: 1441923195
Обложка/Формат: Paperback
Страницы: 672
Вес: 1.02 кг.
Дата издания: 2005
Серия: Springer Series in Statistics
Язык: English
Издание: Softcover reprint of
Иллюстрации: Black & white illustrations
Размер: 234 x 156 x 34
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. The book builds on recent developments, both at the foundational level and the computational level, to present a self-contained view.


Causal Inference for Statistics, Social, and Biomedical Sciences

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Essential Statistical Inference

Автор: Boos
Название: Essential Statistical Inference
ISBN: 1461448174 ISBN-13(EAN): 9781461448174
Издательство: Springer
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Цена: 15372.00 р.
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Описание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.

Methods for estimation and inference in modern econometrics

Автор: Anatolyev, Stanislav Gospodinov, Nikolay
Название: Methods for estimation and inference in modern econometrics
ISBN: 1439838240 ISBN-13(EAN): 9781439838242
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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Описание:

Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.





Topics covered include:







  • Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference


  • Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models


  • Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences






Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.

Models for Probability and Statistical Inference -  Theory and Applications

Автор: Stapleton
Название: Models for Probability and Statistical Inference - Theory and Applications
ISBN: 0470073721 ISBN-13(EAN): 9780470073728
Издательство: Wiley
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Цена: 22802.00 р.
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Описание: Serving as a text for a two semester sequence on probability and statistical inference complex Models for Probability and Statistical Inference: Theory and Applications features exercises throughout the book and selected answers (not solutions). Each section is followed by a selection of problems, from simple to more complex.

Probability and statistical inference

Автор: Bartoszynski, Robert Niewiadomska-bugaj, Magdalena
Название: Probability and statistical inference
ISBN: 0471696935 ISBN-13(EAN): 9780471696933
Издательство: Wiley
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Цена: 22810.00 р.
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Описание: Introduces probability and statistical concepts through non-trivial, real-world examples. This title promotes the development of intuition rather than simple application. Covering the advancements in computer-intensive methods, it provides the tools needed to develop an understanding of the theory of statistics and its probabilistic foundations.


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