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Non-parametric test for decreasing renewal dichotomous Markov noise shock model

Author

Listed:
  • Renjith Mohan

    (Indian Statistical Institute)

  • Sreelakshmi N

    (Prajyoti Niketan College)

  • Sudheesh K. Kattumannil

    (Indian Statistical Institute)

Abstract

Sepehrifar and Yarahmadian (Stat Pap 58:1115–1124, 2017) had developed a non-parametric test for testing exponentiality against decreasing renewal dichotomous Markov noise shock model (DRDMNS) alternatives which when subjected to scrutiny under delivers. Hence, we propose a non-parametric test for testing exponentiality against a class of distributions belonging to DRDMNS models. The asymptotic properties of the test statistic are discussed. An exact null distribution is derived and critical values with different sample sizes are obtained. The proposed test is applied to the censored data also. The results of the Monte Carlo simulations are used to further manifest the quality of the proposed test. Finally, the proposed test is illustrated using two real data sets.

Suggested Citation

  • Renjith Mohan & Sreelakshmi N & Sudheesh K. Kattumannil, 2022. "Non-parametric test for decreasing renewal dichotomous Markov noise shock model," Statistical Papers, Springer, vol. 63(3), pages 965-982, June.
    • Handle: RePEc:spr:stpapr:v:63:y:2022:i:3:d:10.1007_s00362-021-01264-x
    DOI: 10.1007/s00362-021-01264-x
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    References listed on IDEAS

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    1. Somnath Datta & Dipankar Bandyopadhyay & Glen A. Satten, 2010. "Inverse Probability of Censoring Weighted U‐statistics for Right‐Censored Data with an Application to Testing Hypotheses," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(4), pages 680-700, December.
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