Efficient MCMC for temporal epidemics via parameter reduction

Computational Statistics and Data Analysis

Volumn 80, Issue , 2014, Pages 240-250

  Xiang, Fei ^a   Neal, Peter ^a  

^a LANCASTER UNIVERSITY   (United Kingdom)

Author keywords

Adaptive MCMC; Data augmentation; Foot and mouth disease; SIR epidemic models; Smallpox

Indexed keywords

EPIDEMIOLOGY;

ADAPTIVE MCMC; DATA AUGMENTATION; FOOT-AND-MOUTH DISEASE; SIR EPIDEMIC MODEL; SMALLPOX;

ALGORITHMS;

EID: 84905023308     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2014.07.002     Document Type: Article

References (18)

1. N.T.J. Bailey The Mathematical Theory of Infectious Diseases and its Applications second ed. 1975 Griffin London
2. T. Britton, T. Kypraios, and P.D. O'Neill Inference for epidemics with three levels of mixing: methodology and application to a measles outbreak Scand. J. Statist. 38 2011 578 599
3. T. Britton, and P.D. O'Neill Bayesian inference for stochastic epidemics in populations with random social structure Scand. J. Statist. 29 2002 375 390
4. G.J. Gibson Markov chain monte carlo methods for fitting spatiotemporal stochastic models in plant epidemiology J. R. Stat. Soc. Ser. A 46 2 1997 215 233 (Pubitemid 127367872)
5. C.P. Jewell, T. Kypraios, P. Neal, and G.O. Roberts Bayesian analysis for emerging infectious diseases Bayesian Anal. 4 4 2009 465 496
6. M.J. Keeling, M.E.J. Woolhouse, D.J. Shaw, L. Matthews, M. Chase-Topping, D.T. Haydon, S.J. Cornell, J. Kappey, J. Wilesmith, and B.T. Grenfell Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape Science 294 5543 2001 813 817 (Pubitemid 33032092)
7. T. Kypraios Efficient Bayesian Inference for Partially Observed Stochastic Epidemics and a New Class of Semi-parametric Time Series Models (Ph.D. thesis) 2007 Department of Mathematics and Statistics, Lancaster University Lancaster
8. J.S. Liu The collapsed Gibbs sampler in Bayesian computations with applications to a gene regulation problem J. Amer. Statist. Assoc. 89 1994 958 966
9. T.J. McKinley, J.V. Ross, R. Deardon, and A.R. Cook Simulation-based Bayesian inference for epidemic models Comput. Statist. Data Anal. 71 2014 434 447
10. P. Neal, and G.O. Roberts A case study in non-centering for data augmentation: stochastic epidemics Stat. Comput. 15 2005 315 327 (Pubitemid 41442619)
11. P.D. O'Neill Bayesian inference for stochastic multitype epidemics in structured populations using sample data Biostatistics 10 4 2009 779 791
12. P.D. O'Neill, and N.G. Becker Inference for an epidemic when susceptibility varies Biostatistics 2 1 2001 99 108 (Pubitemid 33253772)
13. P.D. O'Neill, and G.O. Roberts Bayesian inference for partially observed stochastic epidemics J. R. Stat. Soc. Ser. A 162 1999 121 129
14. O. Papaspiliopoulos, G.O. Roberts, and M. Sköld Non-centred parametrisations for hierarchical models and data augmentation J.M. Bernardo, M.J. Bayarri, J.O. Berger, A.P. Dawid, D. Heckerman, A.F.M. Smith, M. West, Bayesian Statistics 7 2003 Oxford University Press New York 307 326
15. G.O. Roberts, A. Gelman, and W.R. Gilks Weak convergence and optimal scaling of random walk metropolis algorithms Ann. Appl. Probab. 7 1997 110 120
16. G.O. Roberts, and J.S. Rosenthal Optimal scaling of discrete approximations to Langevin diffusions J. R. Stat. Soc. Ser. B 60 1998 255 268 (Pubitemid 128656507)
17. UK National Audit Office, 2002. The 2001 outbreak of foot and mouth disease. Comptroller and auditor general, HC939, Session 2001-2002, The Stationary Office, London.
18. T. Xifara Bayesian Inference on a Coupled Hidden Markov Model for Disease Interactions and a New Position Dependent Metropolis Adjusted Langevin Algorithm (Ph.D. thesis) 2013 Department of Mathematics and Statistics, Lancaster University