A general and fast convergent bandwidth selection method of kernel estimator

Ibrahim A. Ahmad, Mohamed Amezziane

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


A new method of bandwidth estimation is developed in this article. It has the attractive property of controlled rate of convergence, regardless of sample size. This approach is applied in different contexts of functional estimation leading to bandwidth selectors that enjoy minimal assumptions, are easy to compute and have fast orders of convergence. The method is presented to jointly apply to the density, its derivatives and the distribution functions, all in one setting, and is used then to deliver bandwidth selectors in estimating density derivative functionals.

Original languageEnglish
Pages (from-to)165-187
Number of pages23
JournalJournal of Nonparametric Statistics
Issue number4-5
StatePublished - May 2007
Externally publishedYes


  • Bandwidth selection
  • M-estimation
  • Nonparametric functional estimation
  • Rate of convergence
  • U-statistics


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