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.
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.
"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. https://doi.org/10.1214/23-BJPS582