A multi-criterion evaluation approach to selection of the best statistical distribution

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)165-180
Journal / PublicationComputers and Industrial Engineering
Volume47
Issue number2-3
Publication statusPublished - Nov 2004

Abstract

Using traditional statistical analysis methods one chooses a hypothesized distribution to describe the observed data, estimate the distribution parameters, and then apply the Kolmogorov-Smirnov test statistic Dmax or the Chi-square test statistic χ2 to test the goodness of fit. Observing that the Dmax statistic considers only the information on cumulative distribution function (CDF), we have proposed a multi-criterion decision-making approach considering not only the Dmax statistic but also the errors in CDF, the errors in probability distribution function, the errors in skewness and kurtosis, and experts' preference. A case study is provided to illustrate the use of the proposed approach. © 2004 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Decision-making, Goodness of fit, Hypothesis testing, Multicriterion, Statistics