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dc.contributor.advisorRolke, Wolfgang A.
dc.contributor.authorGutierrez, Cristian
dc.date.accessioned2019-08-12T15:50:59Z
dc.date.available2019-08-12T15:50:59Z
dc.date.issued2019-07-10
dc.identifier.urihttps://hdl.handle.net/20.500.11801/2503
dc.description.abstractOne of the most commonly used goodness-of-fit tests is based on Pearson's chi-square statistic. Since this requires class intervals for the data, questions arise with respect to the method of estimation, types, and the number of classes to use. In one dimension, standard recommendations are to use intervals with the same probability or the same size. A combination of these two was studied, and a method that automatically finds the optimal bin type and the number of bins is presented. To make this possible, an improved computational tool is also presented.en_US
dc.language.isoenen_US
dc.subjectKolmogorov-Smirnov;en_US
dc.subjectAnderson-Darling;en_US
dc.subjectPoweren_US
dc.subject.lcshGoodness-of-fit testsen_US
dc.subject.lcshChi-square testen_US
dc.subject.lcshDistribution (Probability theory)en_US
dc.titleBinning in the chi-square goodness-of-fit testen_US
dc.typeThesisen_US
dc.rights.holder(c) 2019 Cristian Fernando Gutiérrez Góngoraen_US
dc.contributor.committeeLorenzo-Gónzalez, Edgardo
dc.contributor.committeeSantana-Morant, Dámaris
dc.contributor.representativeFrederick-Agosto, Just
thesis.degree.levelM.S.en_US
thesis.degree.disciplineMathematical Statisticsen_US
dc.contributor.collegeCollege of Arts and Sciences - Sciencesen_US
dc.contributor.departmentDepartment of Mathematicsen_US
dc.description.graduationSemesterSummeren_US
dc.description.graduationYear2019en_US


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    Items included under this collection are theses, dissertations, and project reports submitted as a requirement for completing a degree at UPR-Mayagüez.

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(c) 2019 Cristian Fernando Gutiérrez Góngora
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