Summary
This paper outlines the recent development of a general theory of quai–likelihood which embraces the principal features of the methods of least squares and maximum likelihood.
Résumé
Cet article expose le developpement nouveau de une théorie générale de quasi–vraisemblance. par où on embrasse les méthods de moindre carrés et de maximum de vraisemblance.
Chapter PDF
Similar content being viewed by others
Key words
References
Durbin, J. (1960). Estimation of parameters in time-series regression models. JR. Statist. Soc. B 22, 139–153.
Fisher, R.A. (1912). On an absolute criterion for fitting frequency curves. Messeng. Math. 41, 155–160.
Fisher, R.A. (1920). A mathematical examination of the methods of determining the accuracy of an observation by the mean error, and by the mean square error. Mon. Not. Roy. Astron. Soc. 80, 758–770.
Fisher, R.A. (1922). On the mathematical foundations of theoretical statistics. Phil. Trans. A 222, 309–368.
Fisher, R.A. (1925). Theory of statistical estimation. Proc.Camb. Phil. Soc. 22, 700–725.
Godambe, V.P. (1960). An optimal property of regular maximum likelihood estimation. Ann. Math. Statist. 31, 1208–1212.
Godambe, V.P. and Heyde, C.C. (1987). Quasi-likelihood and optimal estimation. Int. Statist. Rev. 55, 231–244.
Grenander, U. (1981) Abstract Inference. Wiley, New York.
Heyde, C.C. (1987). On combining quasi-likelihood estimating functions. Stoch. Processes Applic. 25, 281–287.
Heyde, C.C. (1988) Fixed sample and asymptotic optimality for classes of estimating functions. Contemporary Mathematics 80, 241–247.
Heyde, C.C. (1989) On efficiency for quasi-likelihood and composite quasi-likelihood methods. In Proceedings of International Conference on Recent Developments in Statistical Data Analysis and Inference, Neuchátel, August 1989. Elsevier, Amsterdam, to appear.
Heyde, C.C. and Gay, R. (1989). On asymptotic quasi-likelihood estimation. Stock. Processes. Applic. 31, in press.
Lindsay, B.G. (1988). Composite likelihood methods. Contemporary Mathematics 80, 221–239.
McCullagh, P. and Neider, J.A. (1983) Generalized Linear Models. Chapman and Hall, London.
McLeish, D.L. and Small, C.G. (1988). The Theory and Application of Statistical Inference Functions. Springer Lecture Notes in Statistics No. 44, Springer, New York.
Pearson, K. (1894). Contributions to the mathematical theory of evolution. Phil. Trans. Roy.Soc. A. 185,71–110.
Sorensen, M. (1989). On quasi-likelihood for semimartingales. Stoch. Processes Applic., to appear.
Thavaneswaran, A. (1986). Estimations of Semimartingales. PhD thesis, University of Waterloo, Canada.
Wedderburn, R.W.M. (1974). Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method. Biometrika 61, 439–447.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer New York
About this chapter
Cite this chapter
Heyde, C.C. (2010). Fisher Lecture. In: Maller, R., Basawa, I., Hall, P., Seneta, E. (eds) Selected Works of C.C. Heyde. Selected Works in Probability and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5823-5_50
Download citation
DOI: https://doi.org/10.1007/978-1-4419-5823-5_50
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-5822-8
Online ISBN: 978-1-4419-5823-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)