A Hierarchical Model for Space–Time Surveillance Data on Meningococcal Disease Incidence

DOI10.1111/1467-9876.00396zbMath1111.62347OpenAlexW2118754020WikidataQ60373480 ScholiaQ60373480MaRDI QIDQ3435750

Sylvia Richardson, Leonhard Knorr-Held

Publication date: 7 May 2007

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00396

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Numerical analysis or methods applied to Markov chains (65C40)

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Cites Work

• Unnamed Item
• Fast Sampling of Gaussian Markov Random Fields
• Analysis of time series subject to changes in regime
• Conditional Prior Proposals in Dynamic Models
• Analyses of Infectious Disease Data from Household Outbreaks by Markov Chain Monte Carlo Methods
• Bayesian Measures of Model Complexity and Fit
• Bayesian Inference in Hidden Markov Models Through the Reversible Jump Markov Chain Monte Carlo Method

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