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Approximate Bayesian inference for discretely observed continuous‐time multi‐state models

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Publication:5214572
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DOI10.1111/BIOM.13019zbMath1436.62641OpenAlexW2910559903WikidataQ91069593 ScholiaQ91069593MaRDI QIDQ5214572

Andrea Tancredi

Publication date: 7 February 2020

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.13019


zbMATH Keywords

Markov modelWeibullBayesian inferencemodel choicesemi-Markovsequential Monte-Carlo


Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Reliability and life testing (62N05) Sequential estimation (62L12) Markov processes: hypothesis testing (62M02)


Related Items (3)

On predictive inference for intractable models via approximate Bayesian computation ⋮ Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs ⋮ Bayesian inference for continuous-time hidden Markov models with an unknown number of states







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