Stats, Volume 8, Issue 3
2025 September - 35 articles
Cover Story: A Markov chain Monte Carlo (MCMC)-based Bayesian methodology is proposed and applied to the phase-type aging model (PTAM), with a view to improving parameter estimability. The proposed method provides two methodological extensions based on an existing MCMC inference method. First, we propose a two-level MCMC sampling scheme that is applicable to scenarios where the posterior distributions do not take simple forms after data augmentation. Secondly, an existing data augmentation technique for Bayesian inference on continuous phase-type distributions is further developed in order to incorporate left-truncated data. The proposed methodology improves parameter estimability via sound prior distributions and may also be utilized as a stand-alone statistical model-fitting technique. View this paper
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Stats - ISSN 2571-905X