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dc.contributor.supervisor Davies, Katherine (Statistics) en_US
dc.contributor.author White, Josie
dc.date.accessioned 2014-06-26T14:19:59Z
dc.date.available 2014-06-26T14:19:59Z
dc.date.issued 2014-06-26
dc.identifier.uri http://hdl.handle.net/1993/23665
dc.description.abstract In goodness-of-fit testing, the goal is to determine if data come from a particular distribution. One graphical approach to test goodness-of-fit is a probability plot. Two probability plots typically used are the probability-probability plot and the quantile-quantile plot, but to use these plots, plotting points are needed. Balakrishnan et al. (2010) proposed a new plotting point based on simultaneous closeness probabilities. This was followed up by a correlation-type goodness-of-fit test based on these plotting points. In this thesis, two tests based on the correlation coefficient test are proposed; in particular, a maximal-correlation coefficient test and a minimal-correlation coefficient test which are based on simultaneous closeness probabilities are developed. Two approaches are considered to investigate these two tests: a grid search method and an averaging method. Numerical results, including illustrative examples, critical values and a power study are also provided. en_US
dc.subject Pitman Closeness en_US
dc.title A minimal-maximal correlation-type goodness-of-fit test en_US
dc.degree.discipline Statistics en_US
dc.contributor.examiningcommittee Yang, Po (Statistics) Balakrishnan, Narayanaswamy (McMaster University) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note October 2014 en_US


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