Nonlinear Regression

by George A.F. Seber, Christopher J. Wild

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.

768 pages, Kindle Edition

First published February 1, 1989