A nonparametric test for scale in univariate population two-sample setup

Sunil Mathur, Samuel Dolo

Research output: Contribution to journalArticle

Abstract

A new method is proposed for testing the equality of two populations in a scale model. The power of the proposed test is compared using the Monte Carlo simulation technique with the Siegel-Tukey test [26], the Klotz score test [16], and Levene's test [18]. Simulation studies show that the proposed test performs better than Siegel-Tukey's test, the Klotz score test, and Levene's test under almost all the distributions considered in the study. We calculate the asymptotic relative efficiency of the proposed test. We apply the proposed test to a real life situation.

Original languageEnglish (US)
Pages (from-to)145-152
Number of pages8
JournalModel Assisted Statistics and Applications
Volume2
Issue number3
StatePublished - Dec 1 2007

Fingerprint

Non-parametric test
Univariate
Testing
Levene's Test
Score Test
Asymptotic Relative Efficiency
Monte Carlo simulation
Equality
Monte Carlo Simulation
Simulation Study
Calculate

Keywords

  • Data
  • Efficiency
  • Power
  • Rank
  • Scale
  • Test

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Applied Mathematics

Cite this

A nonparametric test for scale in univariate population two-sample setup. / Mathur, Sunil; Dolo, Samuel.

In: Model Assisted Statistics and Applications, Vol. 2, No. 3, 01.12.2007, p. 145-152.

Research output: Contribution to journalArticle

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