Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations

Gérard Collomb and Wolfgang Härdle

Stochastic Processes and their Applications, 1986, vol. 23, issue 1, 77-89

Abstract: Let be a strictly stationary real valued time series. We predict ZN + 1 from {Z1,...ZN} by a robust nonparametric method. The predictor is defined by the kernel method and constructed as a functional M-estimate connected with the conditional law of Zp+1 on Z1,...,Zp, when is Markovian of order p. Strong uniform convergence rates of this estimate are given together with some new results concerning robust regression kernel estimates from a sequence of valued, identically distributed and [phi]-mixing random pairs {(Xi, Yi); I = 1,...,n}. As a special case we obtain strong uniform convergence rates for estimators of the regression curve E(Y1/X1 = ·) and of the density of the law of X1.

Keywords: robust; time; series; analysis; robust; prediction; robust; nonparametric; regression; M-estimation; rate; of; convergence; kernel; estimate; nonparametric; regression; and; density; estimation (search for similar items in EconPapers)
Date: 1986
References: Add references at CitEc
Citations: View citations in EconPapers (30)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(86)90017-7
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:23:y:1986:i:1:p:77-89

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().