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.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/23665 |
| Date | 26 June 2014 |
| Creators | White, Josie |
| Contributors | Davies, Katherine (Statistics), Yang, Po (Statistics) Balakrishnan, Narayanaswamy (McMaster University) |
| Source Sets | University of Manitoba Canada |
| Detected Language | English |
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