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Optimal estimation of parameters /

"This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a generalized maximum capacity estimator. This approach allows the optimal estimation of real-valued parameters, their number and intervals, as well as providing common ground for...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Rissanen, Jorma (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge : Cambridge University Press, 2012.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Optimal estimation of parameters /  |c Jorma Rissanen, Tampere University of Technology, Helsinki Institute for Information Technology. 
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520 |a "This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a generalized maximum capacity estimator. This approach allows the optimal estimation of real-valued parameters, their number and intervals, as well as providing common ground for explaining the power of these estimators. Beginning with a review of coding and the key properties of information, the author goes on to discuss the techniques of estimation and develops the generalized maximum capacity estimator, based on a new form of Shannon's mutual information and channel capacity. Applications of this powerful technique in hypothesis testing and denoising are described in detail. Offering an original and thought-provoking perspective on estimation theory, Jorma Rissanen's book is of interest to graduate students and researchers in the fields of information theory, probability and statistics, econometrics and finance"--  |c Provided by publisher 
505 0 |a Cover; OPTIMAL ESTIMATION OF PARAMETERS; Title; Copyright; Contents; Preface; 1: Introduction; Part I: Coding and information; 2: Basics of coding; 2.1 Coding and probability; 2.2 Coding and entropy; 2.3 Huffman's code; 2.4 Codes as number representations; 2.4.1 Arithmetic codes; 3: Basics of information; 3.1 Main definitions; 3.2 Mutual information; 3.2.1 Expected mutual information; 3.2.2 Maximum estimation information; Part II: Estimation; 4: Modeling problems; 4.1 Models; 4.2 General comments on estimation; 4.3 Maximum capacity; 4.4 Necessary conditions for optimality. 
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