Graphical tools to assess goodness-of-fit in non-location-scale distributions

Translated title of the contribution: Graphical tools to assess goodness-of-fit in non-location-scale distributions

Claudia Castro Kuriss, Víctor Leiva, Emilia Athayde

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Goodness-of-fit (GOF) techniques are used for assessment whether a distribution is suitable to describe a data set or not. These techniques have been studied for distributions belonging to the location-scale family. However, one could be interested in making this assessment for distributions that do not belong to this family. We review the available GOF tests and propose graphical tools based on these tests for censored and uncensored data from non-location-scale distributions. Anderson-Darling, Cramér-von Mises, Kolmogorov-Smirnov, Kuiper, Michael and Watson GOF statistics are considered. We apply the proposed results to real-world data sets to illustrate their potential, with emphasis on some Birnbaum-Saunders distributions.

Translated title of the contributionGraphical tools to assess goodness-of-fit in non-location-scale distributions
Original languageEnglish
Pages (from-to)341-365
Number of pages25
JournalRevista Colombiana de Estadistica
Volume37
Issue number2
DOIs
StatePublished - 2014
Externally publishedYes

Keywords

  • Censored data
  • Confidence band
  • Data analysis
  • Probability plots

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