Assessing the Impact of a Movement Network on the Spatiotemporal Spread of Infectious Diseases
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Publication:4649048
DOI10.1111/j.1541-0420.2011.01717.xzbMath1272.62083OpenAlexW2152270492WikidataQ45041547 ScholiaQ45041547MaRDI QIDQ4649048
Håvard Rue, Birgit Schrödle, Leonhard Held
Publication date: 19 November 2012
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1541-0420.2011.01717.x
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Uses Software
Cites Work
- A general science-based framework for dynamical spatio-temporal models
- Surveillance: An R package for the monitoring of infectious diseases
- Posterior simulation and Bayes factors in panel count data models
- Estimation and extrapolation of time trends in registry data -- borrowing strength from related populations
- Auxiliary mixture sampling for parameter-driven models of time series of counts with applications to state space modelling
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Markov Regression Models for Time Series: A Quasi-Likelihood Approach
- A statistical framework for the analysis of multivariate infectious disease surveillance counts
- A Hierarchical Model for Space–Time Surveillance Data on Meningococcal Disease Incidence
- A regression model for time series of counts
- Markov chain Monte Carlo for dynamic generalised linear models
- Time Series Models Based on Generalized Linear Models: Some Further Results
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Bayesian analysis of a time series of counts with covariates: an application to the control of an infectious disease
- Predictive Model Assessment for Count Data