A Simple Empirical Likelihood Ratio Test for Normality Based on the Moment Constraints of a Half-Normal Distribution
Joint Authors
Source
Journal of Probability and Statistics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A simple and efficient empirical likelihood ratio (ELR) test for normality based on moment constraints of the half-normal distribution was developed.
The proposed test can also be easily modified to test for departures from half-normality and is relatively simple to implement in various statistical packages with no ordering of observations required.
Using Monte Carlo simulations, our test proved to be superior to other well-known existing goodness-of-fit (GoF) tests considered under symmetric alternative distributions for small to moderate sample sizes.
A real data example revealed the robustness and applicability of the proposed test as well as its superiority in power over other common existing tests studied.
American Psychological Association (APA)
Marange, C. S.& Qin, Y.. 2018. A Simple Empirical Likelihood Ratio Test for Normality Based on the Moment Constraints of a Half-Normal Distribution. Journal of Probability and Statistics،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1197702
Modern Language Association (MLA)
Marange, C. S.& Qin, Y.. A Simple Empirical Likelihood Ratio Test for Normality Based on the Moment Constraints of a Half-Normal Distribution. Journal of Probability and Statistics No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1197702
American Medical Association (AMA)
Marange, C. S.& Qin, Y.. A Simple Empirical Likelihood Ratio Test for Normality Based on the Moment Constraints of a Half-Normal Distribution. Journal of Probability and Statistics. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1197702
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197702