Abstract
Asymptotic optimality of estimating functions—Efficient estimation (cf. Efficient estimator) of parameters in stochastic models is most conveniently approached via properties of estimating functions, namely functions of the data and the parameter of interest, rather than estimators derived therefrom. For a detailed explanation see [3, Chapt. 1].
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Godambe, V.P., AND Heyde, C.C.: ‘Quasi-likelihood and optimal estimation’, Internat. Statist. Rev. 55 (1987), 231–244.
Heyde, C.C.: Quasi-likelihood and its application. A general approach to optimal parameter estimation, Springer, 1997.
McLeish, D.L., and Small, C.G.: The theory and applications of statistical inference functions, Lecture Notes in Statistics. Springer, 1988.
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Heyde, C.C. (2010). Asymptotic Optimality. 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_53
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