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Numerical Methods for Nonlinear Estimating Equations (Oxford Statistical Science Series, 29) free ebook download.

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 extensivecoverage 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 thesealgorithms. 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 ofexamples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student.

ISBN: 0198506880, Author: Christopher G. Small, Publisher: Oxford University Press, USA, Pages: 328, Publication Date: 2003-12-11


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