ASYMPTOTICS FOR THE DISTRIBUTION FUNCTION ESTIMATORS OF THE ERRORS IN SEMI-PARAMETRIC REGRESSION MODELS

This paper considers the convergence rates for nonparametric estimators of the error distribution in semi-parametric regression models. By establishing some general laws of the iterated logarithm, it shows that the rates of convergence of either the empirical distribution or a smoothed version of th...

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Veröffentlicht in:	Journal of systems science and complexity 2014-04, Vol.27 (2), p.360-369
Hauptverfasser:	Qiu, Yuyang, Fu, Keang, Huang, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Complex Systems Control Mathematics Mathematics and Statistics Mathematics of Computing Operations Research/Decision Theory Statistics Systems Theory 分布估计半参数回归模型收敛速度模型误差独立样本经验分布函数误差分布非参数估计
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Beschreibung
Zusammenfassung:	This paper considers the convergence rates for nonparametric estimators of the error distribution in semi-parametric regression models. By establishing some general laws of the iterated logarithm, it shows that the rates of convergence of either the empirical distribution or a smoothed version of the empirical distribution function matches exactly the rates obtained for an independent sample from the error distribution.
ISSN:	1009-6124 1559-7067
DOI:	10.1007/s11424-014-2255-1