Finite-sample performance of convex optimization algorithms in empirical likelihood ratio-based goodness-of-fit test statistics

The finite-sample performance of convex optimization algorithms for the empirical likelihood methodology has been assessed using an empirical likelihood ratio (ELR) based test statistic for normality. Using the R statistical package, a Monte Carlo simulation approach was adopted to compare various f...

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Bibliographic Details

Published in:	Journal of statistical computation and simulation Vol. 95; no. 15; pp. 3330 - 3352
Main Author:	Marange, Chioneso Show
Format:	Journal Article
Language:	English
Published:	Taylor & Francis 13.10.2025
Subjects:	algorithms Convex optimization empirical likelihood goodness-of-fit normality
ISSN:	0094-9655, 1563-5163
Online Access:	Get full text
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