Economics at your fingertips  

Asymptotic normality of an adaptive kernel density estimator for finite mixture models

R.J. Karunamuni, T.N. Sriram and JunJie Wu

Statistics & Probability Letters, 2006, vol. 76, issue 2, 211-220

Abstract: Choice of an appropriate kernel density estimator is a difficult one in minimum distance estimation based on density functions. Particularly, for mixture models, the choice of bandwidth is very crucial because the component densities may have different scale parameters, which in turn necessitate varying amount of smoothing. Adaptive kernel density estimators use different bandwidths for different components, which make them an ideal choice for minimum distance estimation in mixture models. Cutler and Cordero-Braña (1996. Minimum Hellinger distance estimates for parametric models. J. Amer. Stat. Assoc. 91, 1716-1721) introduced such an adaptive kernel density estimator in their work on minimum Hellinger distance estimation of mixture parameters. In this paper, we study a general version of their adaptive kernel density estimator and establish the asymptotic normality of the proposed estimator. We also illustrate the performance of our estimator via a small simulation study.

Keywords: Adaptive; kernel; density; estimator; Minimum; Hellinger; distance; estimation; Asymptotic; normality (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
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:

Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01

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 Haili He ().

Page updated 2020-09-11
Handle: RePEc:eee:stapro:v:76:y:2006:i:2:p:211-220