M-estimation in nonparametric regression under strong dependence and infinite variance

Ngai Hang Chan; Rongmao Zhang

doi:10.1007/s10463-007-0142-4

M-estimation in nonparametric regression under strong dependence and infinite variance

Ngai Hang Chan, Rongmao Zhang

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Citations (Scopus)

Abstract

A robust local linear regression smoothing estimator for a nonparametric regression model with heavy-tailed dependent errors is considered in this paper. Under certain regularity conditions, the weak consistency and asymptotic distribution of the proposed estimators are obtained. If the errors are short-range dependent, then the limiting distribution of the estimator is normal. If the data are long-range dependent, then the limiting distribution of the estimator is a stable distribution. © 2007 The Institute of Statistical Mathematics, Tokyo.

Original language	English
Pages (from-to)	391-411
Journal	Annals of the Institute of Statistical Mathematics
Volume	61
Issue number	2
DOIs	https://doi.org/10.1007/s10463-007-0142-4
Publication status	Published - Jun 2009
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Heavy-tailed
Long-range dependence
M-estimation
Nonparametric regression
Stable distribution

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10.1007/s10463-007-0142-4

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title = "M-estimation in nonparametric regression under strong dependence and infinite variance",

abstract = "A robust local linear regression smoothing estimator for a nonparametric regression model with heavy-tailed dependent errors is considered in this paper. Under certain regularity conditions, the weak consistency and asymptotic distribution of the proposed estimators are obtained. If the errors are short-range dependent, then the limiting distribution of the estimator is normal. If the data are long-range dependent, then the limiting distribution of the estimator is a stable distribution. {\textcopyright} 2007 The Institute of Statistical Mathematics, Tokyo.",

keywords = "Heavy-tailed, Long-range dependence, M-estimation, Nonparametric regression, Stable distribution",

author = "Chan, {Ngai Hang} and Rongmao Zhang",

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T1 - M-estimation in nonparametric regression under strong dependence and infinite variance

AU - Chan, Ngai Hang

AU - Zhang, Rongmao

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2009/6

Y1 - 2009/6

N2 - A robust local linear regression smoothing estimator for a nonparametric regression model with heavy-tailed dependent errors is considered in this paper. Under certain regularity conditions, the weak consistency and asymptotic distribution of the proposed estimators are obtained. If the errors are short-range dependent, then the limiting distribution of the estimator is normal. If the data are long-range dependent, then the limiting distribution of the estimator is a stable distribution. © 2007 The Institute of Statistical Mathematics, Tokyo.

AB - A robust local linear regression smoothing estimator for a nonparametric regression model with heavy-tailed dependent errors is considered in this paper. Under certain regularity conditions, the weak consistency and asymptotic distribution of the proposed estimators are obtained. If the errors are short-range dependent, then the limiting distribution of the estimator is normal. If the data are long-range dependent, then the limiting distribution of the estimator is a stable distribution. © 2007 The Institute of Statistical Mathematics, Tokyo.

KW - Heavy-tailed

KW - Long-range dependence

KW - M-estimation

KW - Nonparametric regression

KW - Stable distribution

UR - http://www.scopus.com/inward/record.url?scp=65449181628&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-65449181628&origin=recordpage

U2 - 10.1007/s10463-007-0142-4

DO - 10.1007/s10463-007-0142-4

M3 - RGC 21 - Publication in refereed journal

SN - 0020-3157

VL - 61

SP - 391

EP - 411

JO - Annals of the Institute of Statistical Mathematics

JF - Annals of the Institute of Statistical Mathematics

IS - 2

ER -

M-estimation in nonparametric regression under strong dependence and infinite variance

Abstract

Bibliographical note

Research Keywords

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