Bayesian inference: Weibull Poisson model for censored data using the expectation–maximization algorithm and its application to bladder cancer data

DOI10.1080/02664763.2020.1845626OpenAlexW3105842306MaRDI QIDQ5085669

Anurag Pathak, Manoj Kumar, Sanjay Kumar Singh, Umesh Singh

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1845626

zbMATH Keywords

likelihood ratio testexpectation-maximization algorithmBayes predictionexpected experiment timeGELFPT-II CBRs

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• BayesDA

Cites Work

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• Statistical Analysis of a Weibull Extension Model
• A new compounding life distribution: the Weibull–Poisson distribution
• Bayesian and maximum likelihood estimations of the inverse Weibull parameters under progressive type-II censoring
• Progressively Censored Samples in Life Testing

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