Advances in Decision Sciences
Volume 5 (2001), Issue 3, Pages 181-191
doi:10.1155/S117391260100013X
Power of the Neyman smooth tests for the uniform distribution
Glen D. Rayner1
and John C. Rayner2
1School of Computing and Mathematics, Deakin University, Waurn Ponds, VIC3217, Australia
2School of Mathematics and Applied Statistics, University of Wollongong, NSW2522, Australia
Abstract
This paper compares and investigates the generalised Neyman smooth test, its components, and the classical chi-squared test with a variety of equiprobable classes. Each test is evaluated in terms of its power to reject a wavelike alternative to the uniform distribution, chosen to quantify the complexity of the alternative. Results indicate that if broadly focused tests (rather than strongly directional or weakly omnibus) are sought, then smooth tests of order about four, or the chi-squared test with between five and ten classes, will perform well.