Estimation of location and scale parameters based on kernel functional estimators

Ibrahim A. Ahmad; Mohamed Amezziane

doi:10.1142/9789814340564_0001

Estimation of location and scale parameters based on kernel functional estimators

Ibrahim A. Ahmad, Mohamed Amezziane

Statistics, Actuarial & Data Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Scopus citations

Abstract

In this paper we present new estimators of location and scale parameters that are constructed based on kernel estimators of the distribution functionals. We investigate the asymptotic behavior of the estimators under different sets of weak moment conditions and we devise a simple method to obtain the optimal bandwidth for the kernel function. The theoretical results are supported by a simulation study of the estimators' small sample performance.

Original language	English
Title of host publication	Nonparametric Statistics and Mixture Models
Subtitle of host publication	A Festschrift in Honor of Thomas P Hettmansperger
Publisher	World Scientific Publishing Co.
Pages	1-14
Number of pages	14
ISBN (Electronic)	9789814340564
ISBN (Print)	9814340553, 9789814340557
DOIs	https://doi.org/10.1142/9789814340564_0001
State	Published - Jan 1 2011

Keywords

Asymptotic distribution
Kernel estimation
Location and scale parameters
Smoothing parameter

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10.1142/9789814340564_0001

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AB - In this paper we present new estimators of location and scale parameters that are constructed based on kernel estimators of the distribution functionals. We investigate the asymptotic behavior of the estimators under different sets of weak moment conditions and we devise a simple method to obtain the optimal bandwidth for the kernel function. The theoretical results are supported by a simulation study of the estimators' small sample performance.

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KW - Location and scale parameters

KW - Smoothing parameter

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ER -

Estimation of location and scale parameters based on kernel functional estimators

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Keywords

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