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

Chi Yang Chu, Daniel J. Henderson, Christopher Parmeter

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)199-214
Number of pages16
JournalEconometrics
Volume3
Issue number2
DOIs
StatePublished - Jun 1 2015

Keywords

  • Bandwidth selection
  • Discrete variable
  • Kernel
  • Nonparametric
  • Plug-in

ASJC Scopus subject areas

  • Economics and Econometrics

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