Powers of Discrete Goodness-of-Fit Test Statistics for a Uniform Null Against a Selection of Alternative Distributions
Author(s)
Steele, Michael
Chaseling, Janet
Griffith University Author(s)
Year published
2006
Metadata
Show full item recordAbstract
The comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov-Smirnov, Cram鲭von Mises, and Anderson-Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearson's chi-square and the nominal Kolmogorov-Smirnov) and circular data (Watson's test statistic) are shown to be generally more powerful for the investigated triangular (?), flat (or ...
View more >The comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov-Smirnov, Cram鲭von Mises, and Anderson-Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearson's chi-square and the nominal Kolmogorov-Smirnov) and circular data (Watson's test statistic) are shown to be generally more powerful for the investigated triangular (?), flat (or platykurtic type), sharp (or leptokurtic type), and bimodal alternative distributions.
View less >
View more >The comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov-Smirnov, Cram鲭von Mises, and Anderson-Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearson's chi-square and the nominal Kolmogorov-Smirnov) and circular data (Watson's test statistic) are shown to be generally more powerful for the investigated triangular (?), flat (or platykurtic type), sharp (or leptokurtic type), and bimodal alternative distributions.
View less >
Journal Title
Communications in Statistics - Simulation and Computation
Volume
35
Subject
Mathematical sciences
Information and computing sciences