Generalized Quasi-Likelihood Methods

M. Ataharul Islam () and Soma Chowdhury Biswas ()
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M. Ataharul Islam: University of Dhaka, ISRT
Soma Chowdhury Biswas: University of Chittagong, Department of Statistics

Chapter Chapter 10 in Generalized Linear Models and Extensions, 2025, pp 189-196 from Springer

Abstract: Abstract Quasi-likelihood methods are a flexible way of modeling multivariate data without specifying the full distribution. They only require the specification of the mean and variance functions, and a dispersion parameter. These methods have been introduced by Wedderburn (Biometrika 61:439–447, 1974), but have not received much attention in the context of multivariate models, such as GEE models and GLMM. This chapter will present the extension of quasi-likelihood methods to multivariate data, and discuss the quasi-likelihood functions, estimating equations, quasi deviances, and model tests based on them.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-4726-2_10

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DOI: 10.1007/978-981-96-4726-2_10

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