Empirical characteristic function approach to goodness of fit tests for the logistic distribution under SRS and RSS

M. T. Alodat, S. A. Al-Subh, Kamarulzaman Ibrahim, Abdul Aziz Jemain

Research output: Contribution to journalArticle

Abstract

The integral of the squares modulus of the difference between the empirical characteristic function and the characteristic function of the hypothesized distribution is used by Wong and Sim (2000) to test for goodness of fit. A weighted version of Wong and Sim (2000) under ranked set sampling, a sampling technique introduced by McIntyre (1952), is examined. Simulations that show the ranked set sampling counterpart of Wong and Sim (2000) is more powerful.

Original languageEnglish
Pages (from-to)558-567
Number of pages10
JournalJournal of Modern Applied Statistical Methods
Volume9
Issue number2
Publication statusPublished - Nov 2010

Fingerprint

Empirical Characteristic Function
Ranked Set Sampling
Logistics/distribution
Goodness of Fit Test
Goodness of fit
Characteristic Function
Modulus
Simulation
Goodness of fit test
Empirical characteristic function
Sampling

Keywords

  • Empirical distribution function
  • Goodness of fit test
  • Logistic distribution
  • Ranked set sampling
  • Simple random sampling

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

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abstract = "The integral of the squares modulus of the difference between the empirical characteristic function and the characteristic function of the hypothesized distribution is used by Wong and Sim (2000) to test for goodness of fit. A weighted version of Wong and Sim (2000) under ranked set sampling, a sampling technique introduced by McIntyre (1952), is examined. Simulations that show the ranked set sampling counterpart of Wong and Sim (2000) is more powerful.",
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