Likelihood and quasi - likelihood estimation of transition probabilities

• Autorzy: Ewa Bakinowska , Radosław Kala
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

likelihood estimation; quasi-likelihood estimation; transition probabilities; quasi-information matrix

Kategorie tematyczne

• 62F05: Asymptotic properties of tests
• 62F10: Point estimation

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2004
• Tom: 24
• Numer: 1
• Strony: 77-84

Daty

wydano

2004

otrzymano

2003-10-04

Twórcy

autor

Ewa Bakinowska

• Department of Mathematical and Statistical Methods, Agricultural University of Poznań, Wojska Polskiego 28, PL 60637 Poznań, Poland

autor

Radosław Kala

• 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.

Identyfikatory

DOI

10.7151/dmps.1047