An Empirical Likelihood Ratio Test for Normality

2007/01/30 by Lauren Bin Dong, David E. A. Giles · 2 citations
Engineering · Mathematics · #Advanced Statistical Methods and Models #Econometrics #Engineering #Likelihood-ratio test #Mathematics #Monte Carlo method #Normality #Normality test #Range (aeronautics) #Ratio test #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference #Statistical hypothesis testing #Statistics #Test (biology)

paper · doi:10.1080/03610910601096544

openalex publication_date 2007/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this article. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range of alternative distributions show that the ELR test is the most powerful of these tests in certain situations.

Citations

• An Extension of Shapiro and Wilk's W Test for Normality to Large Samples
• Large Sample Properties of Generalized Method of Moments Estimators
• THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED
• An analysis of variance test for normality (complete samples)
• X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling
• Efficient tests for normality, homoscedasticity and serial independence of regression residuals
• Empirical likelihood ratio confidence intervals for a single functional

Cited by

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