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1996•Chinese Journal of Applied Probability and StatistiesRequires access

Some Results on Asymptotic Efficiency in A Generalized Serniparametric Regression Model

Hua Liang, Gao J

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Abstract

Consider Y = f(X,β0) + g(T) + e. f(.,.) is a given function defined on Rb1 x Rp, g(.) is an unknown smooth function, β0 is a p x 1 vector to be estimated. This paper summerizes the known results on asymptotic normality, efficiency under the sense of asymptotic normality, second order asymptotic efficiency ans Bahadur asymptotic efficiency of the estimates of β0.

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What this paper is about

Consider Y = f(X,β0) + g(T) + e. f(.,.) is a given function defined on Rb1 x Rp, g(.) is an unknown smooth function, β0 is a p x 1 vector to be estimated. This paper summerizes the known results on asymptotic normality, efficiency under the sense of asymptotic normality, second order asymptotic efficiency ans Bahadur asymptotic efficiency of the estimates of β0.

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Available abstract

Consider Y = f(X,β0) + g(T) + e. f(.,.) is a given function defined on Rb1 x Rp, g(.) is an unknown smooth function, β0 is a p x 1 vector to be estimated. This paper summerizes the known results on asymptotic normality, efficiency under the sense of asymptotic normality, second order asymptotic efficiency ans Bahadur asymptotic efficiency of the estimates of β0.

Key concepts: Mathematics, Asymptotic distribution, Local asymptotic normality, Asymptotic analysis, Function (biology), Normality, Applied mathematics, Statistics

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