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September 10, 2025AxiomsOpen Access

Failure Cause Analysis Under Progressive Type-II Censoring Using Generalized Linear Exponential Competing Risks Model with Medical and Industrial Applications

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Analysis reveals effective parameter estimation in competing risks datasets, suggesting robust applications in various fields.

The proposed model estimates unknown parameters effectively, enhancing the analysis of failure causes.
Using maximum likelihood and bootstrap methods, the model provides confidence intervals for survival indices.
A comprehensive simulation study supports the reliability of the proposed estimation methods across datasets.
Real-world applications demonstrate the practicality of the model in both medical and industrial contexts.

Alhidairah et al. (2025) studied this question.

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