Numerical Methods for Nonlinear Estimating Equations (Oxford Statistical Science, Vol. 29) - Hardcover

Small, Christopher G.; Wang, Jinfang

Hardcover

ISBN 10: 0198506880 ISBN 13: 9780198506881

Publisher: Oxford University Press, 2003

Synopsis

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.

About this title

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.

Edition details

• Publisher: Oxford University Press
• Publication date: 2003
• Language: English
• ISBN 10: 0198506880
• ISBN 13: 9780198506881
• Binding: Hardcover
• Edition number: 1
• Number of pages: 324