September 2023 Inference for a competing risks model with Burr XII distributions under generalized progressive hybrid censoring
Prakash Chandra, Amulya Kumar Mahto, Yogesh Mani Tripathi
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Braz. J. Probab. Stat. 37(3): 566-595 (September 2023). DOI: 10.1214/23-BJPS582


This article considers the inference for a competing risks model with a partially observed failure cause when latent failure times follow Burr XII distributions. Inference is obtained under a generalized progressive hybrid censoring. Estimations of unknown parameters under different restrictions are provided using frequentist and Bayesian approaches. Subsequently, interval estimators are also derived. Bayesian estimators are developed for order-restricted parameters and are compared with corresponding likelihood estimators. The case of unrestricted parameters is considered as well. The performance of all estimators is evaluated based on a simulation study, and a real data set is also presented for illustrative purposes.

Funding Statement

The research work of Yogesh Mani Tripathi is partially supported under a grant MTR/2022/ 000183.


The authors wish to thank the Editor, an Associate Editor and anonymous referees for their valuable suggestions which led to the significant improvement in content and presentation of the paper.


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Prakash Chandra. Amulya Kumar Mahto. Yogesh Mani Tripathi. "Inference for a competing risks model with Burr XII distributions under generalized progressive hybrid censoring." Braz. J. Probab. Stat. 37 (3) 566 - 595, September 2023.


Received: 1 July 2023; Accepted: 1 August 2023; Published: September 2023
First available in Project Euclid: 22 November 2023

Digital Object Identifier: 10.1214/23-BJPS582

Keywords: Bayes estimate , competing risks model , credible interval , generalized progressive hybrid censoring , maximum likelihood estimate , order restriction

Rights: Copyright © 2023 Brazilian Statistical Association


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Vol.37 • No. 3 • September 2023
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