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期刊论文

Statistical inference on parametric part for partially linear single-index model

张日权ZHANG RiQuan† & HUANG ZhenSheng

Science in China Series A: Mathematics Oct., 2009, Vol. 52, No. 10, 2227-2242,-0001,():

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摘要/描述

Statistical inference on parametric part for the partially linear single-index model (PLSIM) is considered in this paper. A profile least-squares technique for estimating the parametric part is proposed and the asymptotic normality of the profile least-squares estimator is given. Based on the estimator, a generalized likelihood ratio (GLR) test is proposed to test whether parameters on linear part for the model is under a contain linear restricted condition. Under the null model, the proposed GLR statistic follows asymptotically the χ2-distribution with the scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Both simulated and real data examples are used to illustrate our proposed methods.

版权说明:以下全部内容由张日权上传于   2011年01月04日 11时27分31秒,版权归本人所有。

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