Abstract
In this article, our objective is to evaluate the performance of different tests which are used to compare the equality of more than two location parameters. We have considered six tests (including some commonly used) in this study, one of which is parametric and the others are nonparametric. These tests include the usual F test (Fisher and Mackenzie, 1923), Kruskal-Wallis test (Kruskall and Wallis, 1952), Kolmogorov-Smirnov test (David, 1958), the g test (Stekler, 1987), f test (Batchelor, 1990), and Extension of Median test (as given in Daniel, 1990). Performance of these tests are compared under different symmetric, skewed and contaminated probability distributions that include Normal, Cauchy, Uniform, Laplace, Lognormal, Exponential, Weibull, Gamma, t, Chi-square, Half Normal, Mixed Weibull, and Mixed Normal. Performances of these tests are measured in terms of power. We have suggested appropriate tests which may perform better under different situations. It is expected that researchers will find these results useful in decision making.
| Original language | English |
|---|---|
| Pages (from-to) | 839-853 |
| Number of pages | 15 |
| Journal | Communications in Statistics Part B: Simulation and Computation |
| Volume | 40 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jul 2011 |
Keywords
- Location parameters
- Nonparametric and parametric tests
- Normality and non normality
- Power
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
Fingerprint
Dive into the research topics of 'Performance evaluation of different tests for location parameters'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver