Generalized linear models

A - Papers appearing in refereed journals

Nelder, J. A. and Wedderburn, R. W. M. 1972. Generalized linear models. Journal of the Royal Statistical Society, Series A (Statistics in Society). 135 (3), pp. 370-384. https://doi.org/10.2307/2344614

AuthorsNelder, J. A. and Wedderburn, R. W. M.
Abstract

The technique of iterative weighted linear regression can be used to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation. A generalization of the analysis of variance is given for these models using log-likelihoods. These generalized linear models are illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables) and gamma (variance components). The implications of the approach in designing statistics courses are discussed.

KeywordsRRES175; 175_Statistics
Year of Publication1972
JournalJournal of the Royal Statistical Society, Series A (Statistics in Society)
Journal citation135 (3), pp. 370-384
Digital Object Identifier (DOI)https://doi.org/10.2307/2344614
Open accessPublished as bronze (free) open access
Output statusPublished
Copyright licensePublisher copyright
ISSN0964-1998
PublisherWiley-Blackwell

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