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dc.contributor.authorMonti, Gianna S.
dc.contributor.authorMateu Figueras, Gloria
dc.contributor.authorOrtego Martínez, María Isabel
dc.contributor.authorPawlowsky Glahn, Vera
dc.contributor.authorEgozcue Rubí, Juan José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.identifier.citationMonti, G. S., Mateu, G., Ortego, M.I., Pawlowsky, V., Egozcue, J. J. Modified Kolmogorov-Smirnov test of goodness of fit. A: International Workshop on Compositional Data Analysis. "The 7th International Workshop on Compositional Data Analysis Proceedings book". Abbadia San Salvatore: 2017, p. 152-158.
dc.description.abstractA modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a specified, although arbitrary, probability model is unsuitable to describe the underlying distribution of a set of observations. The KS test computes distances between points of the sample cumulative distribution function and the hypothetical one as absolute differences between them, and then considering the supreme distance as test statistics. The modification here proposed consists of computing the mentioned distances as Aitchison distances of the probabilities as two part compositions. In this contribution, we investigate by simulation the asymptotic distribution of the proposed test statistic, checking the appropriateness of the Gumbel distribution. The properties of the asymptotic distribution are studied for samples coming from generic distributions such as uniform, normal, lognormal, gamma, beta and exponential with different values of the parameters. A brief Monte Carlo investigation is made of the type I error and power of the test.
dc.format.extent7 p.
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.lcshDistribution (Probability theory)
dc.titleModified Kolmogorov-Smirnov test of goodness of fit
dc.typeConference report
dc.subject.lemacDistribució (Teoria de la probabilitat)
dc.contributor.groupUniversitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorMonti, G. S.; Mateu, G.; Ortego, M.I.; Pawlowsky, V.; Egozcue, J. J.
local.citation.contributorInternational Workshop on Compositional Data Analysis
local.citation.pubplaceAbbadia San Salvatore
local.citation.publicationNameThe 7th International Workshop on Compositional Data Analysis Proceedings book

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