first
prev
toc
Download Citation
Recommend
Mark
Alert
Link
Print
Asymptotic normality of spline estimator when the errors are a linear stationary process
Authors:
Beno
t Truong-Van a;
Noëlle Bru b
t Truong-Van a;
Noëlle Bru b
| Affiliations: | a Lahomtoire de Statistique et Pmbabilit s, Universit Paul Sabatier, Toulouse, France |
| b Laboratoire de Statistique et d'Analyse des Donnes, Universit Pierre Mends, Grenoble, France |
DOI:
10.1080/10485250108832875
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
PDF
(English)
Article Requests:
Order Reprints
:
Request Permissions
-
Single Article Purchase:
US$37.00
-
buy now
-
Sign In
- Online Sample
add to cart 
[ show other buying options ]
View Article:
View Article (PDF)
Abstract
Smoothing splines are considered for estimating an unknown regular function when the errors in the observations are dependent This dependence is modelled here by assuming that the errors form a linear stationary process defined over some sequence of martingale differences. Some statistical properties of the smoothing spline estimator under consideration are studied and mainly its asymptotic normality is established
|
| Keywords: Spline regression; Martingale differences; Linear stationary process; Asymptotic normality |
| view references (23) |
|
Bookmark with:
|
CiteULike
Del.icio.us
BibSonomy
Connotea
More bookmarks
