An improved data-based algorithm for choosing the window width when estimating the density at a point

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54 Scopus citations

Abstract

Sheather [3] proposed a data-based algorithm for choosing the window width when estimating the density at a point by a kernel estimator. Unfortunately, for some densities the windows widths produced by the algorithm have considerable bias. More importantly the resulting density estimator is not scale invariant. In this note we show how a modification to the algorithm overcomes these two problems.

Original languageEnglish
Pages (from-to)61-65
Number of pages5
JournalComputational Statistics and Data Analysis
Volume4
Issue number1
DOIs
StatePublished - Jun 1986

Keywords

  • Kernel density estimation
  • Smoothing parameter

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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