- Title
- Simulated power of the discrete Cramer-von Mises goodness-of-fit tests
- Creator
- Steele, Mike; Chaseling, Janet; Hurst, Cameron
- Date
- 2005
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/54085
- Identifier
- vital:1580
- Identifier
- http://www.mssanz.org.au/modsim05/papers/steele.pdf
- Identifier
- ISBN:0975840029
- Abstract
- The use of goodness-of-fit test statistics for discrete or categorical data is widespread throughout the research community with the Chi- Square the most popular when a researcher aims to determine if observed categorical data differs from a hypothesized multinomial distribution. Even for ordinal categorical data, the use of empirical distribution function (EDF) test statistics such as the Kolmogorov-Smirnov, the three Cramér-von Mises (A2, W2 and U2 as defined below) and various modifications of these are limited in the literature. Power studies of the EDF type test statistics are even more limited. This paper compares the simulated power of the three Cramér-von Mises test statistics with that of the Chi-Square test statistic for a uniform null hypothesis against a variety of alternative distributions which are summarized in Figure 1. Recommendations are made on which is the most powerful test statistic for the predefined alternative distributions.; E1
- Publisher
- Melbourne : The Modelling and Simulation Society of Australia and New Zealand Inc.
- Relation
- Paper presented at MODSIM 2005: International Congress of Modelling and Simulation, Advances and Applications for Management and Decision Making, Melbourne : 12th -15th December, 2005 p. 1300-1304
- Rights
- Open Access
- Rights
- Copyright Modelling and Simulation Society of Australia and New Zealand Inc.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Goodness of fit; Power; Empirical distribution function
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