R: Generalized Nonlinear Models

gnm-package {gnm} | R Documentation

## Generalized Nonlinear Models

### Description

Functions to specify, fit and evaluate generalized nonlinear models.

### Details

`gnm` provides functions to fit generalized nonlinear models by maximum likelihood. Such models extend the class of generalized linear models by allowing nonlinear terms in the predictor.

Some special cases are models with multiplicative interaction terms, such as the UNIDIFF and row-column association models from sociology and the AMMI and GAMMI models from crop science; stereotype models for ordered categorical response, and diagonal reference models for dependence on a square two-way classification.

`gnm` is a major re-working of an earlier Xlisp-Stat package, "Llama". Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.

The following documentation provides further information on the `gnm` package:

gnmOverview

  `vignette("gnmOverview", package = "gnm")`

NEWS

  `file.show(system.file("NEWS", package = "gnm"))`

### Author(s)

Heather Turner and David Firth

Maintainer: Heather Turner <ht@heatherturner.net>

### References

http://www.warwick.ac.uk/go/gnm

### See Also

`gnm` for the model fitting function, with links to associated functions.

### Examples

    demo(gnm)

[Package gnm version 1.0-8 Index]