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From the Reviews of Nonlinear Regression
"A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; and I would imagine that any statistician concerned with nonlinear regression would want a copy on his shelves."
–The Statistician
"Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher."
–Mathematical Reviews
"synopsis" may belong to another edition of this title.
From the Publisher:
This text/reference provides a broad survey of aspects of model-building and statistical inference. Presents an accessible synthesis of current theoretical literature, requiring only familiarity with linear regression methods. The three chapters on central computational questions comprise a self-contained introduction to unconstrained optimization. Includes many illustrative practical examples.
About the Author:
George A.F. Seber and Christopher J. Wild are professors in the Department of Statistics at The University of Auckland in New Zealand.
"About this title" may belong to another edition of this title.
- PublisherWiley-Interscience
- Publication date2003
- ISBN 10 0471471356
- ISBN 13 9780471471356
- BindingPaperback
- Number of pages800
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