Empirical study of indirect cross-validation

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

In this paper we provide insight into the empirical properties of indirect cross-validation (ICV), a new method of bandwidth selection for kernel density estimators. First, we describe the method and report on the theoretical results used to develop a practical-purpose model for certain ICV parameters. Next, we provide a detailed description of a numerical study which shows that the ICV method usually outperforms least squares cross-validation (LSCV) in finite samples. One of the major advantages of ICV is its increased stability compared to LSCV. Two real data examples show the benefit of using both ICV and a local version of ICV.
22 pages, 21 figures

Keywords

Methodology

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/209205

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0812.0052
 http://arxiv.org/abs/0812.0052

Collections

arXiv