Estimation of integrated squared density derivatives from a contaminated sample

A Delaigle, I Gijbels

Research output: Contribution to journalArticle (Academic Journal)peer-review

48 Citations (Scopus)

Abstract

We propose a kernel estimator of integrated squared density derivatives, from a sample that has been contaminated by random noise. We derive asymptotic expressions for the bias and the variance of the estimator and show that the squared bias term dominates the variance term. This coincides with results that are available for non-contaminated observations. We then discuss the selection of the bandwidth parameter when estimating integrated squared density derivatives based on contaminated data. We propose a data-driven bandwidth selection procedure of the plug-in type and investigate its finite sample performance via a simulation study.
Translated title of the contributionEstimation of integrated squared density derivatives from a contaminated sample
Original languageEnglish
Pages (from-to)869 - 886
Number of pages18
JournalJournal of the Royal Statistical Society: Series B, Statistical Methodology
Volume64 (4)
DOIs
Publication statusPublished - Oct 2002

Bibliographical note

Publisher: Blackwell
Other identifier: IDS number 614ZJ

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