Nonlinear Regression with R
Author: Christian Ritz
Publisher: Springer Science & Business Media
ISBN: 9780387096162
Category: Mathematics
Page: 148
View: 522
Language: en
Pages: 352
Pages: 352
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Language: en
Pages: 148
Pages: 148
- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.
Language: en
Pages: 768
Pages: 768
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future
Language: en
Pages: 258
Pages: 258
The first book to discuss robust aspects of nonlinear regression—with applications using R software Robust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust aspects of nonlinear regression and focuses on outlier effects.
Language: en
Pages: 330
Pages: 330
Let us assume that an observation Xi is a random variable (r.v.) with values in 1 1 (1R1 , 8 ) and distribution Pi (1R1 is the real line, and 8 is the cr-algebra of its Borel subsets). Let us also assume that the unknown distribution Pi belongs to a
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