## Abstract

Generalized linear models are considered within the larger framework of multiparameter exponential family models. This general approach shows that the link function is not a necessary feature of a computer algorithm for calculating maximum likelihood estimates for such models by iteratively reweighted least squares. It is argued that the link function is a useful component of model fitting and interpretation in situations where there is a natural link to an underlying linear model (e. g. , logistic regression). However in many instances there is no single link function (e. g. , multinomial regression) or else unlinked parameters exist (e. g. , bioassay with a spontaneous response rate). It is shown by a number of examples that a general approach via exponential family models is preferable in such situations. 16 refs.

Original language | English (US) |
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Pages (from-to) | 18-24 |

Number of pages | 7 |

Journal | Applied Statistics |

Volume | 33 |

Issue number | 1 |

State | Published - Jan 1 1984 |

Externally published | Yes |

## ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty