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Optimal Estimation of Parameters

Jorma Rissanen
Cambridge ; New York : Cambridge University Press, 2012.
9781107004740 (hardback), 1107004748 (hardback)
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"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"--
  • Basics of coding
  • Basics of information
  • Modeling problems
  • Other optimality properties
  • Interval estimation
  • Hypothesis testing
  • Denoising
  • Sequential models
  • Appendicies. A. Elements of algorithmic information ; B. Universal prior for integers.
vi, 162 p. ; 26 cm.
Includes bibliographical references (p. [156]-160) and index.
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