Mixed Inverse Gaussian Analysis of Covariance for Censored Data: A Bayesian Approach

Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh and Gholamhossein Yari

Journal of Mathematics, 2025, vol. 2025, 1-14

Abstract: This paper proposes a model for analysis of covariance (ANCOVA) of censored data obtained from a positively skewed population by using the mixed inverse Gaussian (MIG) distribution. A hierarchical fully Bayesian approach is employed to fit and infer about the proposed model. For this purpose, a Gibbs sampler algorithm is developed which truly takes into account both the data censoring process and mixture structure of population. A simulation study and a real-world example are worked out to assess and explain the applicability of the proposed methodology.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:1131677

DOI: 10.1155/jom/1131677

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