A - Papers appearing in refereed journals
Wedderburn, R. W. M. 1974. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method. Biometrika. 61 (3), pp. 439-447. https://doi.org/10.1093/biomet/61.3.439
Authors | Wedderburn, R. W. M. |
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Abstract | To define a likelihood we have to specify the form of distribution of the observations, but to define a quasi-likelihood function we need only specify a relation between the mean and variance of the observations and the quasi-likelihood can then be used for estimation. For a one-parameter exponential family the log likelihood is the same as the quasi-likelihood and it follows that assuming a one-parameter exponential family is the weakest sort of distributional assumption that can be made. The Gauss-Newton method for calculating nonlinear least squares estimates generalizes easily to deal with maximum quasi-likelihood estimates, and a rearrangement of this produces a generalization of the method described by Nelder & Wedderburn (1972). |
Keywords | RRES175; 175_Statistics |
Year of Publication | 1974 |
Journal | Biometrika |
Journal citation | 61 (3), pp. 439-447 |
Digital Object Identifier (DOI) | https://doi.org/10.1093/biomet/61.3.439 |
Open access | Published as non-open access |
ISSN | 00063444 |
Publisher | Oxford University Press (OUP) Oxford |
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