Optimal Estimation Of Parameters

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Optimal Estimation of Parameters

Author	: Jorma Rissanen
Publisher	: Cambridge University Press
Total Pages	: 171
Release	: 2012-06-07
ISBN-10	: 9781107004740
ISBN-13	: 1107004748
Rating	: 4/5 (748 Downloads)

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Book Synopsis Optimal Estimation of Parameters by : Jorma Rissanen

Download or read book Optimal Estimation of Parameters written by Jorma Rissanen and published by Cambridge University Press. This book was released on 2012-06-07 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and consistent theory of estimation, including a description of a powerful new tool, the generalized maximum capacity estimator.

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Language: en
Pages: 171

Optimal Estimation of Parameters

Authors: Jorma Rissanen

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A comprehensive and consistent theory of estimation, including a description of a powerful new tool, the generalized maximum capacity estimator.

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Parameter Estimation in Engineering and Science

Authors: James Vere Beck

Categories: Mathematics

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Introduction to and survey of parameter estimation; Probability; Introduction to statistics; Parameter estimation methods; Introduction to linear estimation; Ma

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Optimal State Estimation

Authors: Dan Simon

Categories: Technology & Engineering

Type: BOOK - Published: 2006-06-19 - Publisher: John Wiley & Sons

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A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to est

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Inverse Methods for Atmospheric Sounding

Authors: Clive D. Rodgers

Categories: Science

Type: BOOK - Published: 2000 - Publisher: World Scientific

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Annotation Rodgers (U. of Oxford) provides graduate students and other researchers a background to the inverse problem and its solution, with applications relat

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Model Calibration and Parameter Estimation

Authors: Ne-Zheng Sun

Categories: Mathematics

Type: BOOK - Published: 2015-07-01 - Publisher: Springer

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This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliabili