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中文会议>2008第四届海峡两岸应用统计学术研讨会
>Consistency and asymptotic normality of profile-kernel and backfitting estimators in semiparametric reproductive dispersion nonlinear models
Consistency and asymptotic normality of profile-kernel and backfitting estimators in semiparametric reproductive dispersion nonlinear models
Semiparametric reproductive dispersion nonlinear model(SEDNM)is an extension of reproductive dispersion nonlinear model and semiparametric regression model，and includes semiparametric nonlinear model and semiparametric generalized linear model as its special case. Based on the local kernel estimator of nonparametric component，profile-kernel and backfitting estimators of parameters of interest are proposed in SRDNM，and theoretical comparison of both estimators is also investigated in this article. Under some regularity conditions，strong consistency and asymptotic normality of two estimators are shown.It is shown that the backfitting method produces a larger asymptotic variance than that for the profile-kernel method.
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