Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Novel estimation based on a minimum distance under the progressive Type-II censoring scheme

  • Young Eun Jeon (Department of Statistics, Yeungnam University) ;
  • Suk-Bok Kang (Department of Statistics, Yeungnam University) ;
  • Jung-In Seo (Department of Information Statistics, Andong National University)
  • Received : 2023.01.21
  • Accepted : 2023.03.04
  • Published : 2023.07.31
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Abstract

This paper provides a new estimation equation based on the concept of a minimum distance between the empirical and theoretical distribution functions under the most widely used progressive Type-II censoring scheme. For illustrative purposes, simulated and real datasets from a three-parameter Weibull distribution are analyzed. For comparison, the most popular estimation methods, the maximum likelihood and maximum product of spacings estimation methods, are developed together. In the analysis of simulated datasets, the excellence of the provided estimation method is demonstrated through the degree of the estimation failure of the likelihood-based method, and its validity is demonstrated through the mean squared errors and biases of the estimators obtained from the provided estimation equation. In the analysis of the real dataset, two types of goodness-of-fit tests are performed on whether the observed dataset has the three-parameter Weibull distribution under the progressive Type-II censoring scheme, through which the performance of the new estimation equation provided is examined.

Keywords

Acknowledgement

This work was supported by a grant from 2022 Research Fund of Andong National University

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