A least-squares cross-validation bandwidth selection approach in pair correlation function estimations

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14 Scopus citations

Abstract

The pair correlation function is a useful tool to analyze spatial point patterns. It is often estimated nonparametrically by a procedure such as kernel smoothing. This article develops a data-driven method for the selection of the bandwidth involved in the estimation. The proposed method uses the idea of least-squares cross-validation which has been often applied for bandwidth selection in density estimation and many other nonparametric estimations. The asymptotic property of the proposed approach will be investigated under an increasing-domain setting in this paper.

Original languageEnglish (US)
Pages (from-to)1722-1729
Number of pages8
JournalStatistics and Probability Letters
Volume77
Issue number18
DOIs
StatePublished - Dec 2007
Externally publishedYes

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Keywords

  • Bandwidth selection
  • Least-squares cross-validation
  • Pair correlation function

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

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