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Vague data analysis using neutrosophic Jarque–Bera test

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  • Muhammad Aslam
  • Rehan Ahmad Khan Sherwani
  • Muhammad Saleem

Abstract

In decision-making problems, the researchers’ application of parametric tests is the first choice due to their wide applicability, reliability, and validity. The common parametric tests require the validation of the normality assumption even for large sample sizes in some cases. Jarque-Bera test is among one of the methods available in the literature used to serve the purpose. One of the Jarque-Bera test restrictions is the computational limitations available only for the data in exact form. The operational procedure of the test is helpless for the interval-valued data. The interval-valued data generally occurs in situations under fuzzy logic or indeterminate state of the outcome variable and is often called neutrosophic form. The present research modifies the existing statistic of the Jarque-Bera test for the interval-valued data. The modified design and operational procedure of the newly proposed Jarque-Bera test will be useful to assess the normality of a data set under the neutrosophic environment. The proposed neutrosophic Jarque-Bera test is applied and compared with its existing form with the help of a numerical example of real gold mines data generated under the fuzzy environment. The study’s findings suggested that the proposed test is effective, informative, and suitable to be applied in indeterminacy compared to the existing Jarque–Bera test.

Suggested Citation

  • Muhammad Aslam & Rehan Ahmad Khan Sherwani & Muhammad Saleem, 2021. "Vague data analysis using neutrosophic Jarque–Bera test," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-9, December.
    • Handle: RePEc:plo:pone00:0260689
    DOI: 10.1371/journal.pone.0260689
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    References listed on IDEAS

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    1. Youngseok Choi & Habin Lee & Zahir Irani, 2018. "Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector," Annals of Operations Research, Springer, vol. 270(1), pages 75-104, November.
    2. Van Cutsem, Bernard & Gath, Isak, 1993. "Detection of outliers and robust estimation using fuzzy clustering," Computational Statistics & Data Analysis, Elsevier, vol. 15(1), pages 47-61, January.
    3. Sarat Chandra Nayak & Bijan Bihari Misra, 2019. "A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-34, December.
    4. Thorsten Thadewald & Herbert Buning, 2007. "Jarque-Bera Test and its Competitors for Testing Normality - A Power Comparison," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(1), pages 87-105.
    5. Kim, Namhyun, 2016. "A robustified Jarque–Bera test for multivariate normality," Economics Letters, Elsevier, vol. 140(C), pages 48-52.
    6. Gel, Yulia R. & Gastwirth, Joseph L., 2008. "A robust modification of the Jarque-Bera test of normality," Economics Letters, Elsevier, vol. 99(1), pages 30-32, April.
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