[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.4134/CKMS.2004.19.2.345

ROBUST REGRESSION SMOOTHING FOR DEPENDENT OBSERVATIONS

Kim, Tae-Yoon (Department of Statistics Keimyung University)
Song, Gyu-Moon (Department of Statistics Keimyung University)
Kim, Jang-Han (Department of Statistics Keimyung University)

Publication Information

Communications of the Korean Mathematical Society / v.19, no.2, 2004 , pp. 345-354 More about this Journal

Abstract

Boente and Fraiman [2] studied robust nonparametric estimators for regression or autoregression problems when the observations exhibit serial dependence. They established strong consistency of two families of M-type robust equivariant estimators for $\phi$ -mixing processes. In this paper we extend their results to weaker $\alpha$ $alpha$ -mixing processes.

Keywords

Robust nonparametric regression; strong consistency; $\alpha$ -mixing sequence;

Citations & Related Records

Reference

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