Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme

This article investigates inference in a competing risks model where failure causes are partially observed, assuming latent failure times follow Weibull distributions. Inference is derived under a generalized type-II hybrid censoring scheme. The maximum likelihood estimators for model parameters an...

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Main Authors: G. S. Deepthy, K. K. Anakha, Sebastian Nicy
Format: Article
Language:English
Published: Austrian Statistical Society 2025-05-01
Series:Austrian Journal of Statistics
Online Access:https://www.ajs.or.at/index.php/ajs/article/view/2049
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author G. S. Deepthy
K. K. Anakha
Sebastian Nicy
author_facet G. S. Deepthy
K. K. Anakha
Sebastian Nicy
author_sort G. S. Deepthy
collection DOAJ
description This article investigates inference in a competing risks model where failure causes are partially observed, assuming latent failure times follow Weibull distributions. Inference is derived under a generalized type-II hybrid censoring scheme. The maximum likelihood estimators for model parameters and their associated confidence intervals are discussed. Also, we compute Bayes estimators under both informative and non-informative priors, along with their credible intervals. The performance of all estimators is evaluated through Monte Carlo simulations. Finally, for illustrative purposes, a real-world case is explored.
format Article
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institution DOAJ
issn 1026-597X
language English
publishDate 2025-05-01
publisher Austrian Statistical Society
record_format Article
series Austrian Journal of Statistics
spelling doaj-art-72eb456ec0ec480fa2d220c16bfb83262025-08-20T03:20:05ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2025-05-0154410.17713/ajs.v54i4.2049Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring SchemeG. S. Deepthy0K. K. AnakhaSebastian NicyResearch Scholar This article investigates inference in a competing risks model where failure causes are partially observed, assuming latent failure times follow Weibull distributions. Inference is derived under a generalized type-II hybrid censoring scheme. The maximum likelihood estimators for model parameters and their associated confidence intervals are discussed. Also, we compute Bayes estimators under both informative and non-informative priors, along with their credible intervals. The performance of all estimators is evaluated through Monte Carlo simulations. Finally, for illustrative purposes, a real-world case is explored. https://www.ajs.or.at/index.php/ajs/article/view/2049
spellingShingle G. S. Deepthy
K. K. Anakha
Sebastian Nicy
Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
Austrian Journal of Statistics
title Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
title_full Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
title_fullStr Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
title_full_unstemmed Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
title_short Inference on Partially Observed Competing Risks Models Using Generalized Type-II Hybrid Censoring Scheme
title_sort inference on partially observed competing risks models using generalized type ii hybrid censoring scheme
url https://www.ajs.or.at/index.php/ajs/article/view/2049
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AT kkanakha inferenceonpartiallyobservedcompetingrisksmodelsusinggeneralizedtypeiihybridcensoringscheme
AT sebastiannicy inferenceonpartiallyobservedcompetingrisksmodelsusinggeneralizedtypeiihybridcensoringscheme