Nonparametric M-estimation with long-memory errors

Loading...
Thumbnail Image

Date

2000

Journal Title

Journal ISSN

Volume Title

Publisher

Universitätsbibliothek Dortmund

Abstract

We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind this study is illustrated with an example.

Description

Table of contents

Keywords

Citation