Plug-in bandwidth selection for kernel density estimation with discrete data

Chi Yang Chu; Daniel J. Henderson; Christopher F. Parmeter

doi:10.3390/econometrics3020199

Plug-in bandwidth selection for kernel density estimation with discrete data

Chi Yang Chu, Daniel J. Henderson, Christopher F. Parmeter

Economics

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, in non-uniform designs. We further find that plug-in bandwidths are relatively small. Several empirical examples show that the plug-in bandwidths are typically similar in magnitude to their cross-validated counterparts.

Original language	English (US)
Pages (from-to)	199-214
Number of pages	16
Journal	Econometrics
Volume	3
Issue number	2
DOIs	https://doi.org/10.3390/econometrics3020199
State	Published - Jun 2015

Keywords

Bandwidth selection
Discrete variable
Kernel
Nonparametric
Plug-in

ASJC Scopus subject areas

Economics and Econometrics

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10.3390/econometrics3020199

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AB - This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, in non-uniform designs. We further find that plug-in bandwidths are relatively small. Several empirical examples show that the plug-in bandwidths are typically similar in magnitude to their cross-validated counterparts.

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KW - Nonparametric

KW - Plug-in

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Plug-in bandwidth selection for kernel density estimation with discrete data

Abstract

Keywords

ASJC Scopus subject areas

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