GENERALIZED LINEAR MODELS - THE MISSING LINK.

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish (US)
Title of host publicationApplied Statistics
Pages18-24
Number of pages7
Volume33
Edition1
StatePublished - 1984
Externally publishedYes

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Bioassay
Maximum likelihood
Logistics

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Cox, C. (1984). GENERALIZED LINEAR MODELS - THE MISSING LINK. In Applied Statistics (1 ed., Vol. 33, pp. 18-24)

GENERALIZED LINEAR MODELS - THE MISSING LINK. / Cox, Christopher.

Applied Statistics. Vol. 33 1. ed. 1984. p. 18-24.

Research output: Chapter in Book/Report/Conference proceedingChapter

Cox, C 1984, GENERALIZED LINEAR MODELS - THE MISSING LINK. in Applied Statistics. 1 edn, vol. 33, pp. 18-24.
Cox C. GENERALIZED LINEAR MODELS - THE MISSING LINK. In Applied Statistics. 1 ed. Vol. 33. 1984. p. 18-24
Cox, Christopher. / GENERALIZED LINEAR MODELS - THE MISSING LINK. Applied Statistics. Vol. 33 1. ed. 1984. pp. 18-24
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