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On weighted version of dynamic cumulative residual inaccuracy measure based on extropy

Author

Listed:
  • Morteza Mohammadi

    (University of Zabol)

  • Majid Hashempour

    (University of Hormozgan)

Abstract

This paper introduces the concept of dynamic cumulative residual extropy inaccuracy (DCREI) by expanding on the existing dynamic cumulative residual extropy (DCRE) measure and proposes a weighted version of it. The paper then investigates a characterization problem for the proposed weighted dynamic extropy inaccuracy measure under the proportional hazard model and characterizes some well-known lifetime distributions using the weighted dynamic cumulative residual extropy inaccuracy (WDCREI) measure. Additionally, the study discusses the stochastic ordering of WDCREI and certain results based on it. Non-parametric estimations of the proposed measures based on kernel and empirical estimators are suggested. Results of a simulation study show that the kernel-based estimators perform better than the empirical-based estimator. Finally, applications of the proposed measures on model selection are provided.

Suggested Citation

  • Morteza Mohammadi & Majid Hashempour, 2024. "On weighted version of dynamic cumulative residual inaccuracy measure based on extropy," Statistical Papers, Springer, vol. 65(7), pages 4599-4629, September.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:7:d:10.1007_s00362-024-01568-8
    DOI: 10.1007/s00362-024-01568-8
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    References listed on IDEAS

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    1. Suchandan Kayal & Sunoj S. Madhavan & Rajesh Ganapathy, 2017. "On Dynamic Generalized Measures of Inaccuracy," Statistica, Department of Statistics, University of Bologna, vol. 77(2), pages 133-148.
    2. Quintela-del-Río, Alejandro & Estévez-Pérez, Graciela, 2012. "Nonparametric Kernel Distribution Function Estimation with kerdiest: An R Package for Bandwidth Choice and Applications," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i08).
    3. Lejeune, Michel & Sarda, Pascal, 1992. "Smooth estimators of distribution and density functions," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 457-471, November.
    4. Chanchal Kundu & Asok Nanda, 2015. "Characterizations based on measure of inaccuracy for truncated random variables," Statistical Papers, Springer, vol. 56(3), pages 619-637, August.
    5. Prem Nath, 1968. "Inaccuracy and coding theory," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 13(1), pages 123-135, December.
    6. Murali Rao, 2005. "More on a New Concept of Entropy and Information," Journal of Theoretical Probability, Springer, vol. 18(4), pages 967-981, October.
    7. Qiu, Guoxin & Jia, Kai, 2018. "The residual extropy of order statistics," Statistics & Probability Letters, Elsevier, vol. 133(C), pages 15-22.
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