An Empirical Likelihood Ratio Test for Normality
AbstractThe empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this paper. 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.
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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0401.
Length: 31 pages
Date of creation: 18 Feb 2004
Date of revision:
Note: ISSN 1485-6441
Contact details of provider:
Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
Web page: http://web.uvic.ca/econ
More information through EDIRC
Empirical likelihood; Monte Carlo simulation; testing for normality; size and power;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-23 (All new papers)
- NEP-ECM-2004-02-23 (Econometrics)
- NEP-ETS-2004-02-23 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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