relation: https://episodesplatform.eu/eprints/227/
title: Data-Driven Bandwidth Choice for Density Estimation Based on Dependent Data
creator: Hart, Jeffrey
creator: Vieu, Philippe
subject: Collective properties of seismicity
description: The bandwidth selection problem in kernel density estimation is investigated in situations where the observed data are dependent. The classical leave-out technique is extended, and thereby a class of cross-validated bandwidths is defined. These bandwidths are shown to be asymptotically optimal under a strong mixing condition. The leave-one out, or ordinary, form of cross-validation remains asymptotically optimal under the dependence model considered. However, a simulation study shows that when the data are strongly enough correlated, the ordinary version of cross-validation can be improved upon in finite-sized samples.
publisher: Institute of Mathematical Statistics
date: 1990
type: Article
type: PeerReviewed
identifier:   Hart, Jeffrey and Vieu, Philippe  (1990) Data-Driven Bandwidth Choice for Density Estimation Based on Dependent Data.  The Annals of Statistics, 18 (2).  pp. 873-890. DOI: https://doi.org/10.1214/aos/1176347630 <https://doi.org/10.1214/aos/1176347630>     
relation: http://dx.doi.org/10.1214/aos/1176347630
relation: doi:10.1214/aos/1176347630