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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.
Kategorie tematyczne
Rocznik
Tom
Numer
Strony
77-84
Opis fizyczny
Daty
wydano
2004
otrzymano
2003-10-04
Twórcy
autor
- Department of Mathematical and Statistical Methods, Agricultural University of Poznań, Wojska Polskiego 28, PL 60637 Poznań, Poland
autor
- Department of Mathematical and Statistical Methods, Agricultural University of Poznań, Wojska Polskiego 28, PL 60637 Poznań, Poland
Bibliografia
- [1] D.L. Hawkins and C.-P. Han, Estimating Transition Probabilities from Aggregate Samples Plus Partial Transition Data, Biometrics 56 (2000), 848-854.
- [2] J.D. Kalbfleisch, J.F. Lawless and W.M. Vollomer, Estimation in Markov Models from Aggregate Data, Biometrics 39 (1983), 907-919.
- [3] 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.
- [4] P. McCullagh and J.A. Nelder, Generalized Linear Models, Chapman and Hall, London 1983.
- [5] P. McCullagh and J.A. Nelder, Generalized Linear Models, 2nd. ed. Chapman and Hall, London 1989.
- [6] R.W.M. Wedderburn, Quasi-likelihood Functions, Generalized Linear Models, and the Gauss-Newton method, Biometrika Wedderburn, 61 (1974), 439-447.
Typ dokumentu
Bibliografia
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bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1047