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Progressively Type-II censored competing risks data from the linear exponential distribution

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  • Katherine F. Davies
  • William Volterman

Abstract

Across different types of lifetime studies, whether it be in the medical or engineering sciences, the possibility of competing causes of failures needs to be addressed. Typically referred to as competing risks, in this article we consider progressively type-II censored competing risks data when the lifetimes are assumed to come from a linear exponential distribution. We develop likelihood inference and demonstrate the performance of the estimators via an extensive Monte Carlo simulation study. We also provide an illustrative example using a small data set.

Suggested Citation

  • Katherine F. Davies & William Volterman, 2022. "Progressively Type-II censored competing risks data from the linear exponential distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(5), pages 1444-1460, March.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:5:p:1444-1460
    DOI: 10.1080/03610926.2020.1764044
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    Cited by:

    1. Hanan Haj Ahmad & Mohamed Aboshady & Mahmoud Mansour, 2024. "The Role of Risk Factors in System Performance: A Comprehensive Study with Adaptive Progressive Type-II Censoring," Mathematics, MDPI, vol. 12(11), pages 1-21, June.
    2. Muqrin A. Almuqrin & Mukhtar M. Salah & Essam A. Ahmed, 2022. "Statistical Inference for Competing Risks Model with Adaptive Progressively Type-II Censored Gompertz Life Data Using Industrial and Medical Applications," Mathematics, MDPI, vol. 10(22), pages 1-38, November.

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