A study of the properties of a new goodness-of-fit test
Abstract
We investigate the power properties of a new goodness-of-fit test
proposed by Foutz (1980). This new test is compared with the Chi squared
test and the Kolmogorov-Smirnov (K-S) test for normality when the samples
come from (i) the family of asymmetric stable distributions, (ii) mixtures
of normal distributions, and (iii) the Pearson family. The general conclusion
is that the new test performs better than the Chi squared and the
K-S test when the parent distribution is heavy-tailed. If the hypothesized
distribution differs from the true distribution in location only,
the new test does not do as well as the other two.