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Items: 1 to 20 of 188

1.

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

Charras-Garrido M, Abrial D, Goër JD, Dachian S, Peyrard N.

Biostatistics. 2012 Apr;13(2):241-55. doi: 10.1093/biostatistics/kxr043.

2.

On identification in Bayesian disease mapping and ecological-spatial regression models.

MacNab YC.

Stat Methods Med Res. 2014 Apr;23(2):134-55. doi: 10.1177/0962280212447152.

PMID:
22573502
3.

Poultry, pig and the risk of BSE following the feed ban in France--a spatial analysis.

Abrial D, Calavas D, Jarrige N, Ducrot C.

Vet Res. 2005 Jul-Aug;36(4):615-28.

4.
5.

Combining Monte Carlo and mean-field-like methods for inference in hidden Markov random fields.

Forbes F, Fort G.

IEEE Trans Image Process. 2007 Mar;16(3):824-37.

PMID:
17357740
6.

Spatial heterogeneity of the risk of BSE in France following the ban of meat and bone meal in cattle feed.

Abrial D, Calavas D, Jarrige N, Ducrot C.

Prev Vet Med. 2005 Jan;67(1):69-82.

PMID:
15698909
7.

Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes.

Yue YR, Loh JM.

Biometrics. 2011 Sep;67(3):937-46. doi: 10.1111/j.1541-0420.2010.01531.x.

PMID:
21175553
8.

Approximate inference for disease mapping with sparse Gaussian processes.

Vanhatalo J, Pietiläinen V, Vehtari A.

Stat Med. 2010 Jul 10;29(15):1580-607. doi: 10.1002/sim.3895.

PMID:
20552572
9.

Image segmentation using hidden Markov Gauss mixture models.

Pyun K, Lim J, Won CS, Gray RM.

IEEE Trans Image Process. 2007 Jul;16(7):1902-11.

PMID:
17605387
10.

A stochastic method for Bayesian estimation of hidden Markov random field models with application to a color model.

Destrempes F, Mignotte M, Angers JF.

IEEE Trans Image Process. 2005 Aug;14(8):1096-108.

PMID:
16121458
11.

Modelling of discrete spatial variation in epidemiology with SAS using GLIMMIX.

Rasmussen S.

Comput Methods Programs Biomed. 2004 Oct;76(1):83-9.

PMID:
15313544
12.

A spatio-temporal analysis of BSE cases born before and after the reinforced feed ban in France.

Ducrot C, Abrial D, Calavas D, Carpenter T.

Vet Res. 2005 Sep-Dec;36(5-6):839-53.

13.

Modelling risks in disease mapping.

Ugarte MD, Ibáñez B, Militino AF.

Stat Methods Med Res. 2006 Feb;15(1):21-35.

PMID:
16477946
14.

Fusion of Hidden Markov Random Field models and its Bayesian estimation.

Destrempes F, Angers JF, Mignotte M.

IEEE Trans Image Process. 2006 Oct;15(10):2920-35.

PMID:
17022259
15.
16.

Fuzzy Markov random fields versus chains for multispectral image segmentation.

Salzenstein F, Collet C.

IEEE Trans Pattern Anal Mach Intell. 2006 Nov;28(11):1753-67.

PMID:
17063681
17.

A Bayesian non-parametric Potts model with application to pre-surgical FMRI data.

Johnson TD, Liu Z, Bartsch AJ, Nichols TE.

Stat Methods Med Res. 2013 Aug;22(4):364-81. doi: 10.1177/0962280212448970.

18.

Skew-elliptical spatial random effect modeling for areal data with application to mapping health utilization rates.

Nathoo FS, Ghosh P.

Stat Med. 2013 Jan 30;32(2):290-306. doi: 10.1002/sim.5504.

PMID:
22815268
19.

Turbo segmentation of textured images.

Lehmann F.

IEEE Trans Pattern Anal Mach Intell. 2011 Jan;33(1):16-29. doi: 10.1109/TPAMI.2010.58.

PMID:
21088316
20.

Latent mixed Markov modelling of smoking transitions using Monte Carlo bootstrapping.

Mannan HR, Koval JJ.

Stat Methods Med Res. 2003 Mar;12(2):125-46.

PMID:
12665207
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