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Estimation of inaccuracy measure for censored dependent data

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  • G. Rajesh
  • E. I. Abdul Sathar
  • K. V. Viswakala

Abstract

In the present paper, we propose non parametric estimators for the inaccuracy measure for the lifetime distribution based on censored data. This measure plays important roles in reliability and survival analysis in connection with modeling and analysis of life time data. Asymptotic properties of the estimators are established under suitable regularity conditions. Monte Carlo simulation studies are carried out to compare the performance of the estimators using the mean-squared error. The methods are illustrated using a real data set.

Suggested Citation

  • G. Rajesh & E. I. Abdul Sathar & K. V. Viswakala, 2017. "Estimation of inaccuracy measure for censored dependent data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(20), pages 10058-10070, October.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:20:p:10058-10070
    DOI: 10.1080/03610926.2016.1228969
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    Cited by:

    1. Kayal, Suchandan, 2018. "Quantile-based cumulative inaccuracy measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 329-344.

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