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:: Volume 17, Issue 1 (9-2023) ::
JSS 2023, 17(1): 0-0 Back to browse issues page
Asymptotic Distribution of ُSome Statistics in Multivariate Inference Based on Taylor Series Expansion
Sakineh Dehghan *
Abstract:   (1628 Views)

The exact distribution of many applicable statistics could not be accessible in various statistical inference problems. To deal with such an issue in the large sample problem, an approach is to obtain the asymptotic distribution. In this article, we have expressed the asymptotic distribution of multivariate statistics class approximated by averages based on the Taylor expansion. Then, the asymptotic distribution of an empirical Mahalanobis depth-based statistic is obtained, and the statistic is applied to test the scale difference between two multivariate distributions. Simulation studies are carried out to explore the behavior of the asymptotic distribution of the test statistic. A real data example illustrating the use of the test is also presented.

Keywords: ‎Multivariate scale test, Taylor‎ series expansion‎, ‎Asymptotic distribution, ‎‎Mahalanobis depth‎‎, ‎Central limit theorem
Full-Text [PDF 325 kb]   (1383 Downloads)    
Type of Study: Research | Subject: Theoritical Statistics
Received: 2022/09/5 | Accepted: 2023/09/1 | Published: 2023/07/11
References
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Dehghan S. Asymptotic Distribution of ُSome Statistics in Multivariate Inference Based on Taylor Series Expansion. JSS 2023; 17 (1)
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 17, Issue 1 (9-2023) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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