Testing Several Correlation Matrices Using Robust Approach
Background and Objective: The performance of classical Jennrich (J) statistic using classical estimators suffers from masking effects. To relieve the problem, robust estimators are recommended. In this study, a robust Jennrich statistic was proposed based on a S estimator (JS) and M estimator (JM) a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Network for Scientific Information
2017
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/24427/1/AJSR%2011%201%202018%2084-95.pdf http://repo.uum.edu.my/24427/ http://doi.org/10.3923/ajsr.2018.84.95 |
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| Summary: | Background and Objective: The performance of classical Jennrich (J) statistic using classical estimators suffers from masking effects. To relieve the problem, robust estimators are recommended. In this study, a robust Jennrich statistic was proposed based on a S estimator (JS) and M estimator (JM) as alternative to the J statistic, which has good properties. Methodology: In the simulation study, the performance of proposed test is assessed in terms of a type I error and the power of test. The performance comparison between classical J, JS and JM statistics are conducted under several conditions. Results: The results of simulation study showed that JS statistic has a competitive performance comparative to a JM statistic and the J statistic. Conclusion: It was concluded that JS statistic is robust for testing the equality of two or more difference correlation matrices when the data contains outlier. © 2018 Shamshuritawati Sharif and Tareq Ahmed Mahmoud Atiany. |
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