JOURNAL BROWSE
Search
Advanced SearchSearch Tips
ROBUST REGRESSION SMOOTHING FOR DEPENDENT OBSERVATIONS
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
ROBUST REGRESSION SMOOTHING FOR DEPENDENT OBSERVATIONS
Kim, Tae-Yoon; Song, Gyu-Moon; Kim, Jang-Han;
  PDF(new window)
 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 -mixing processes. In this paper we extend their results to weaker -mixing processes.
 Keywords
Robust nonparametric regression;strong consistency;-mixing sequence;
 Language
English
 Cited by
 References
1.
J. Multivariate Anal., 1989. vol.29. pp.180-198 crossref(new window)

2.
Ann. Statist., 1989. vol.17. pp.1242-1256 crossref(new window)

3.
Zeit. Wahr. ver. Geb, 1984. vol.66. pp.441-460 crossref(new window)

4.
Stochastic Process. Appl., 1984. vol.56. pp.151-159 crossref(new window)

5.
Stochastic Process. Appl., 1995. vol.56. pp.151-159 crossref(new window)

6.
C. R. Acad. Sci. Paris Ser. Ⅰ Math., 1985. vol.298. pp.305-308

7.
Theory Probab. Appl., 1964. vol.9. pp.141-412 crossref(new window)

8.
J. Time Ser. Anal., 1983. vol.4. pp.185-207 crossref(new window)

9.
Lecture Notes in Statist., 1984. vol.26. pp.247-265 crossref(new window)

10.
Sankhya Ser. A, 1964. vol.26. pp.359-372