Testing Uniformity Via Log-Spline Modeling

Abstract

The data driven method of selecting the number of components in Neyman's smooth test for uniformity, introduced by Ledwina (1994) and generalized by Kallenberg and Ledwina (1995a), is extended to cover some log-spline models. Asymptotic null distribution is derived and consistency of the data driven test is shown under essentially all alternatives. Some simulation results are also presented.

Keywords:

• AMS subject classifications
• 62G10
• 62E20
• 62E25

Keywords:

• Goodness-of-fit
• >smooth test
• >Neyman's test. Schwarz's BIC criterion
• >splines
• >exponential family
• >Monte Carlo power