Data-Driven Bandwidth Choice for Density Estimation Based on Dependent Data

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

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1214/aos/1176347630

Abstract

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.

[error in script]
Item Type: Article
Subjects: Methodology > Method and procesing > Collective properties of seismicity
Project: IS-EPOS project