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Numerical Methods for Nonlinear Estimating Equations PDF

322 Pages·2003·2.456 MB·English
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by Christopher G. Small, Jinfang Wang| 2003| 322 pages| 2.456| English

About Numerical Methods for Nonlinear Estimating Equations

Non linearity 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 likelihood's 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 modification 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.

Detailed Information

Author:Christopher G. Small, Jinfang Wang
Publication Year:2003
ISBN:9780191545092
Pages:322
Language:English
File Size:2.456
Format:PDF
Price:FREE
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Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.