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Can I read A Note on Quasi-likelihood for Exponential Families on EtoBox?
A Note on Quasi-likelihood for Exponential Families by David H. Annis is a Mathematics article available to read on EtoBox.
What is A Note on Quasi-likelihood for Exponential Families about?
Maximum likelihood estimation for exponential families depends exclusively on the first two moments of the data. Recognizing this, Wedderburn [1974. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method. Biometrika 61, 439-447] proposed estimating regression parameters based on a quasi-likelihood function requiring only the relationship between the mean and variance. We extend quasi-likelihood to situations in which there exists vague prior information on the mean parameters. It is shown when data are exponential family with quadratic variance functions, maximum a posteriori inference under a conjugate prior relies solely on two moments of the data and the prior distribution. This result suggests a Bayesian analog of quasi-likelihood for which only two moments of the data and two moments of the prior need be specified.
Who reads A Note on Quasi-likelihood for Exponential Families?
It is typically read by researchers, students, and practitioners in Mathematics.
- Author
- David H. Annis
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0167-7152)
- Published
- 2007
- Language
- EN
- Field
- Mathematics (Physical Sciences)