 Energy statistic-based modified information criterion for detecting the change in distributionJoseph Njuki and Wei Ning Journal of Applied Statistics, 2026, vol. 53, issue 7, 1274-1296 Abstract: In this article, a test to detect the change in the distribution of sequence of independent random variables is proposed. To achieve this, we exploit the relationship between properties of U-statistics and Energy statistics (forms of V-statistics) to come up with a nonparametric test based on modified information criterion (MIC) in the change point detection using Energy statistics (EMIC). To investigate the performance of our proposed (EMIC) method, we assess the finite sample properties and compare efficiencies and powers of different methods with those of our method through simulations. Both the test procedure and the estimator of the location of the change point are consistent under the alternative hypothesis. In addition, simulation studies suggest that the proposed (EMIC) method is superior to other methods especially when the change occurs around the middle of the sequence. We then discuss its applications in two different real-life examples for detecting change in mean and variance. Date: 2026 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:53:y:2026:i:7:p:1274-1296 Ordering information: This journal article can be ordered from DOI: 10.1080/02664763.2025.2555606 Access Statistics for this article Journal of Applied Statistics is currently edited by Robert Aykroyd More articles in Journal of Applied Statistics from Taylor & Francis Journals |
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