ArticleOriginal scientific text
Title
Likelihood and quasi - likelihood estimation of transition probabilities
Authors 1, 1
Affiliations
- Department of Mathematical and Statistical Methods, Agricultural University of Poznań, Wojska Polskiego 28, PL 60637 Poznań, Poland
Abstract
In the paper two approaches to the problem of estimation of transition probabilities are considered. The approach by McCullagh and Nelder [5], based on the independent model and the quasi-likelihood function, is compared with the approach based on the marginal model and the standard likelihood function. The estimates following from these two approaches are illustrated on a simple example which was used by McCullagh and Nelder.
Keywords
likelihood estimation, quasi-likelihood estimation, transition probabilities, quasi-information matrix
Bibliography
- D.L. Hawkins and C.-P. Han, Estimating Transition Probabilities from Aggregate Samples Plus Partial Transition Data, Biometrics 56 (2000), 848-854.
- J.D. Kalbfleisch, J.F. Lawless and W.M. Vollomer, Estimation in Markov Models from Aggregate Data, Biometrics 39 (1983), 907-919.
- T.C. Lee, G.G. Judge and A. Zellender, Estimating the Parameters of the Markov Probability Model from Aggregate Time Series Data, New York, North Holland 1977.
- P. McCullagh and J.A. Nelder, Generalized Linear Models, Chapman and Hall, London 1983.
- P. McCullagh and J.A. Nelder, Generalized Linear Models, 2nd. ed. Chapman and Hall, London 1989.
- R.W.M. Wedderburn, Quasi-likelihood Functions, Generalized Linear Models, and the Gauss-Newton method, Biometrika Wedderburn, 61 (1974), 439-447.
Pages:
77-84
Main language of publication
English
Received
2003-10-04
Published
2004
DOI: 10.7151/dmps.1047
Exact and natural sciences