Analysis for left-truncated and right-censored competing risks data from marshall-olkin bivariate generalized lifetime family

Prakash Chandra (), Arvind Kumar Alok, Yogesh Mani Tripathi and Liang Wang
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Prakash Chandra: Indian Institute of Technology Patna
Arvind Kumar Alok: Indian Institute of Technology (Indian School of Mines) Dhanbad
Yogesh Mani Tripathi: Indian Institute of Technology Patna
Liang Wang: Yunnan Normal University

Computational Statistics, 2025, vol. 40, issue 9, No 30, 5729-5768

Abstract: Abstract In this article, inference for a left-truncated and right-censored competing risk model is discussed when the cause of failures of units is partially observed and dependent. Under the assumption that latent failure times follow the Marshall-Olkin bivariate generalized lifetime distributions, inference for unknown parameters is obtained using frequentist and Bayesian approaches. Maximum likelihood estimators of parameters, along with their existence and uniqueness, are also provided. Subsequently, approximate confidence intervals are constructed based on the observed Fisher information matrix. Further, Bayes estimates and associated highest posterior density credible intervals are developed using a Gamma-Dirichlet prior under squared error and LINEX loss functions. Inference is also discussed with order restrictions on parameters. The performance of various estimators is evaluated based on extensive simulation study, and comments are obtained. Finally, two real-life applications are provided for illustrative purposes.

Keywords: Marshall-Olkin bivariate generalized lifetime distribution; Dependent competing risks model; POGD distribution; MCMC method; HPD credible intervals; Order restriction (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00180-025-01671-w

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