Powerful Goodness-of-fit Tests Based on the Likelihood Ratio

2002/05/01 by Jin Zhang · 2 citations
Computer Science · Mathematics · #Anderson–Darling test #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #Computer science #Construct (python library) #Goodness of fit #Kolmogorov–Smirnov test #Mathematics #Omnibus test #Statistical Methods and Inference #Statistical hypothesis testing #Statistics

paper · doi:10.1111/1467-9868.00337

openalex publication_date 2002/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

Summary A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

Citations

• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
• An analysis of variance test for normality (complete samples)
• A Test of Goodness of Fit
• The Kolmogorov-Smirnov Test for Goodness of Fit

Cited by

• Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy
• Goodness of fit [wikipedia]