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Numerical Methods for Nonlinear Estimating Equations: 29 (Oxford Statistical Science Series) - Hardcover

 
9780198506881: Numerical Methods for Nonlinear Estimating Equations: 29 (Oxford Statistical Science Series)

Synopsis

Nonlinearity arises in statistical inference in various ways, with varying degrees of severity, as an obstacle to statistical analysis. More entrenched forms of nonlinearity often require intensive numerical methods to construct estimators, and the use of root search algorithms, or one-step estimators, is a standard method of solution. This book provides a comprehensive study of nonlinear estimating equations and artificial likelihoods for statistical inference. It provides extensive coverage and comparison of hill climbing algorithms, which, when started at points of nonconcavity often have very poor convergence properties, and for additional flexibility proposes a number
of modifications to the standard methods for solving these algorithms. The book also extends beyond simple root search algorithms to include a discussion of the testing of roots for consistency, and the modification of available estimating functions to provide greater stability in inference. A variety of examples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student.

This is the latest in the well-established and authoritative Oxford Statistical Science Series, which includes texts and monographs covering many topics of current research interest in pure and applied statistics. Each title has an original slant even if the material included is not specifically original. The authors are leading researchers and the topics covered will be of interest to all professional statisticians, whether they be in industry, government department or research institute. Other books in the series include 23. W.J.Krzanowski: Principles of multivariate analysis: a user's perspective updated edition 24. J.Durbin and S.J.Koopman: Time series analysis by State Space Models 25. Peter J. Diggle, Patrick Heagerty, Kung-Yee Liang, Scott L. Zeger: Analysis of Longitudinal Data 2/e 26. J.K. Lindsey: Nonlinear Models in Medical Statistics 27. Peter J. Green, Nils L. Hjort & Sylvia Richardson: Highly Structured Stochastic Systems 28. Margaret S. Pepe: The Statistical Evaluation of Medical Tests for Classification and Prediction

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About the Author

Christopher G. Small is a Professor of Statistics at the University of Waterloo, Canada, and
has been Canada's official representative and Team Leader for the International
Mathematical Olympiad in Taiwan (1998) and Washington (2000).

Jinfang Wang is an Associate Professor in Obihiro University.


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Small, Christopher G.
Published by Oxford University Press, 2003
ISBN 10: 0198506880 ISBN 13: 9780198506881
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Hardback. Condition: Very Good. No Jacket. First edition. 1st 2003. Very good condition with no wrapper. Oxford Statistical Science Series 29. Glazed boards. 309 pages. Spine and corners slightly bumped and rubbed. Small patch of surface paper damage to lower edge of rear cover. 'Damaged' ink stamp to title-page. Packaged with care and promptly dispatched! Seller Inventory # 1319671

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