CriSP: A tool for bump hunting

Jaroslaw Harezlak, Nancy E. Heckman

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

We propose a test of multimodality of regression functions and their derivatives. The test statistic is a critical smoothing parameter (CriSP), giving the minimum amount of smoothing necessary to force the regression function to satisfy the null hypothesis. The p values are computed via bootstrapping. Our idea is motivated by Silverman's test concerning the number of modes in the density function. Simulation studies indicate that the test works well, even when testing for bumps in the derivative. We apply CriSP to children's growth data, to study the number of spurts of gr.

Original languageEnglish (US)
Pages (from-to)713-729
Number of pages17
JournalJournal of Computational and Graphical Statistics
Volume10
Issue number4
DOIs
StatePublished - Dec 2001
Externally publishedYes

Keywords

  • Bootstrap
  • Critical smoothing parameter
  • Growth data
  • Multimodality testing
  • Smoothing

ASJC Scopus subject areas

  • Statistics and Probability
  • Discrete Mathematics and Combinatorics
  • Statistics, Probability and Uncertainty

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