EconPapers    
Economics at your fingertips  
 

A note on the behaviour of a kernel-smoothed kernel density estimator

Paul Janssen, Jan Swanepoel and Noël Veraverbeke

Statistics & Probability Letters, 2020, vol. 158, issue C

Abstract: Kernel density estimators have been studied in great detail. In this note a new family of kernels, depending on a parameter c, is obtained by kernel-smoothing an initial kernel density estimator. Under certain conditions, we show that nonparametric density estimators based on such kernels outperform the initial estimator in terms of minimized asymptotic mean integrated squared error and in kernel efficiency.

Keywords: Asymptotic mean integrated squared error; Kernel density estimator; Kernel efficiency (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715219303098
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:158:y:2020:i:c:s0167715219303098

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2019.108663

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:stapro:v:158:y:2020:i:c:s0167715219303098