Classification method for disease risk mapping based on discrete hidden Markov random fields

Biostatistics

Volumn 13, Issue 2, 2012, Pages 241-255

  Charras Garrido, Myriam ^a   Abrial, David ^a   Goër, Jocelyn De ^a   Dachian, Sergueï ^b   Peyrard, Nathalie ^c  

^a EPIA   (France)

^b UNIVERSITÉ CLERMONT AUVERGNE   (France)

^c CEMAGREF   (France)

Author keywords

Animal epidemiology; Disease mapping; Expectation maximization (EM) algorithm; Image segmentation

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BIOSTATISTICS; BOVINE SPONGIFORM ENCEPHALOPATHY; CATTLE; DISEASES; EPIDEMIOLOGY; FACTUAL DATABASE; FRANCE; HUMAN; MONTE CARLO METHOD; POISSON DISTRIBUTION; PROBABILITY; RISK; RISK FACTOR; STATISTICAL MODEL;

ALGORITHMS; ANIMALS; BIOSTATISTICS; CATTLE; DATABASES, FACTUAL; DISEASE; ENCEPHALOPATHY, BOVINE SPONGIFORM; EPIDEMIOLOGIC METHODS; FRANCE; HUMANS; LINEAR MODELS; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; POISSON DISTRIBUTION; RISK; RISK FACTORS;

ANIMALIA;

EID: 84858032733     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxr043     Document Type: Article

References (19)

1. ABRIAL, D., CALAVAS, D., JARRIGE, N. AND DUCROT, C. (2005). Poultry, pig and the risk of BSE following the feed ban in France-a spatial analysis. Veterinary Research 36, 615-628. (Pubitemid 40960236)
2. ALFO, M., NIEDDU, L. AND VICARI, D. (2009). Finite mixture models for mapping spatially dependent disease counts. Biometrical Journal 52, 84-97.
3. BESAG, J. (1974). Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society Series B 2, 192-236.
4. BESAG, J. (1986). On the statistical analysis of dirty pictures. Journal of the Royal Statistical Society Series B 48, 259-302.
5. BESAG, J., YORK, J. AND MOLLI , A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics 43, 1-59.
6. DEMPSTER, A. P., LAIRD, N. M. AND RUBIN, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society Series B 39, 1-38.
7. FRALEY, C. AND RAFTERY, A. E. (2007). Bayesian regularization for normal mixture estimation and model-based clustering. Journal of Classification 24, 155-181.
8. GREEN, P. J. AND RICHARDSON, S. (2002). Hidden Markov models and disease mapping. Journal of the American Statistical Association 97, 1055-1070. (Pubitemid 36136565)
9. KNORR-HELD, L. AND RASSER, G. (2000). Bayesian detection of clusters and discontinuities in disease maps. Biometrics 56, 13-21. (Pubitemid 30165085)
10. KNORR-HELD, L., RASSER, G. AND BECKER, N. (2002). Disease mapping of stage-specific cancer incidence data. Biometrics 58, 492-501. (Pubitemid 35001466)
11. KNORR-HELD, L. AND RICHARDSON, S. (2003). A hierarchical model for space-time surveillance data on meningococcal disease incidence. Journal of the Royal Statistical Society Series B 52, 169-183. (Pubitemid 37155762)
12. LI, S. Z. (2001). Markov Random Field Modeling in Image Analysis. Computer Science Workbench. London: Springer.
13. MACNAB, Y. C. (2010). On Gaussian Markov random fields and Bayesian disease mapping. Statistical Methods in Medical Research 20, 49-68.
14. MCLACHLAN, G. J. AND KRISHNAN, T. (2008). The EM Algorithm and Extensions, 2nd edition. Hoboken, NJ: Wiley, p. 360.
15. MOLLI, A. (1999). Bayesian and empirical Bayes approaches to disease mapping. In: Lawson, A., Biggeri, A. and Bohning, D. (editors), Disease Mapping and Risk Assessment for Public Health. Chichester: Wiley, pp. 15-29.
16. PASCUTTO, C., WAKEFIELD, J., BEST, N., RICHARDSON, S., BERNARDINELLI, L., STAINES, A. AND ELLIOTT, P. (2000). Statistical issues in the analysis of disease mapping data. Statistics in Medicine 19, 2493-2519.
17. ROBERTSON, C., NELSON, T. A., MACNAB, Y. C. AND LAWSON, A. B. (2010). Review of methods for space-time disease surveillance. Spatial and Spatio-temporal Epidemiology 1, 105-116.
18. WEI, G. C. G. AND TANNER, M. A. (1990). A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms. Journal of the American Statistical Association 85, 411.
19. WU, F. Y. (1982). The Potts model. Reviews of Modern Physics 54, 235-268.