Abstract
S-PLUS has a ‘Modern Regression Module’ which contains functions for a number of regression methods. These are not necessarily non-linear in the sense of Chapter 9, which refers to a non-linear parametrization, but they do allow non-linear functions of the independent variables to be chosen by the procedures. The methods are all fairly computer-intensive, and so are only feasible in the era of plentiful computing power (and hence are ‘modern’). Some of these methods are part of the S modelling language, and others have been added by S-PLUS. As the latter predate the modelling language and have not been updated, the functions of this chapter do not have a consistent style and user interface.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
more precisely A with the (xi) scaled to [0, 1] and the weights scaled to average 1.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Venables, W.N., Ripley, B.D. (1997). Modern Regression. In: Modern Applied Statistics with S-PLUS. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2719-7_11
Download citation
DOI: https://doi.org/10.1007/978-1-4757-2719-7_11
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-2721-0
Online ISBN: 978-1-4757-2719-7
eBook Packages: Springer Book Archive