Robust analysis of variance
For the c -sample location problem with equal and unequal variances, we compare the classical F -test and its robustified version-the Welch test-with some nonparametric counterparts defined for two-sided and one-sided ordered alternatives, such as trend and umbrella alternatives. A new rank test for long-tailed distributions is proposed. The comparison is referred to level alpha and power beta of the tests, and is carried out via Monte Carlo simulation, assuming short-, medium- and long-tailed as well as asymmetric distributions. It turns out that the Welch test is the best one in the case of unequal variances but in the case of equal variances special non-parametric tests are to prefer.
Year of publication: |
1997
|
---|---|
Authors: | Buning, Herbert |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 24.1997, 3, p. 319-332
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Adaptive Jonckheere-type tests for ordered alternatives
BUNing, Herbert, (1999)
-
Adaptive bootstrap tests and its competitors in the c-sample scale problem
Buning, Herbert, (2008)
-
Robustness and power of modified Lepage, Kolmogorov-Smirnov and Cramer-von Mises two-sample tests
Buning, Herbert, (2002)
- More ...