K. Berthelsen and J. Møller, Likelihood and Non-parametric Bayesian MCMC Inference for Spatial Point Processes Based on Perfect Simulation and Path Sampling, Scandinavian Journal of Statistics, vol.62, issue.3, pp.549-564, 2003.
DOI : 10.1002/(SICI)1098-2418(199608/09)9:1/2<223::AID-RSA14>3.0.CO;2-O

J. Besag, Spatial interaction and the statistical analysis of lattice systems (with discussion), J. Roy. Statist. Soc. Ser. B, vol.36, pp.192-236, 1974.

J. Besag and C. Kooperberg, On conditional and intrinsic autoregressions, Biometrika, vol.82, issue.4, pp.733-746, 1995.

J. Besag, J. York, and A. Mollié, Bayesian image restoration, with two applications in spatial statistics, Annals of the Institute of Statistical Mathematics, vol.74, issue.1, 1991.
DOI : 10.1007/BF00116466

P. Bühlmann, Bagging, Boosting and Ensemble Methods, Handbook of Computational Statistics, pp.877-907, 2004.
DOI : 10.1007/978-3-642-21551-3_33

P. Bühlmann and B. Yu, Analyzing bagging, The Annals of Statistics, vol.30, issue.4, pp.927-961, 2002.
DOI : 10.1214/aos/1031689014

P. Bühlmann and B. Yu, Boosting with the L 2 loss: regression and classification, J. Amer. Statist. Assoc, issue.462, pp.98324-339, 2003.

S. Buttrey, Nearest-neighbor classification with categorical variables, Computational Statistics & Data Analysis, vol.28, issue.2, pp.157-169, 1998.
DOI : 10.1016/S0167-9473(98)00032-2

M. Chen, Q. Shao, I. , and J. , Monte Carlo Methods in Bayesian Computation, 2000.
DOI : 10.1007/978-1-4612-1276-8

N. A. Cressie, Statistics for Spatial Data, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics, 1993.

L. Devroye, L. Györfi, and G. Lugosi, A Probabilistic Theory of Pattern Recognition, Applications of Mathematics, vol.31, 1996.
DOI : 10.1007/978-1-4612-0711-5

Y. Freund and R. E. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Second Annual European Conference on Computational Learning Theory (EuroCOLT '95), pp.119-139, 1995.
DOI : 10.1006/jcss.1997.1504

N. Friel, A. Pettitt, R. Reeves, W. , and E. , Bayesian Inference in Hidden Markov Random Fields for Binary Data Defined on Large Lattices, Journal of Computational and Graphical Statistics, vol.18, issue.2, 2005.
DOI : 10.1198/jcgs.2009.06148

N. Friel and A. N. Pettitt, Likelihood Estimation and Inference for the Autologistic Model, Journal of Computational and Graphical Statistics, vol.13, issue.1, pp.232-246, 2004.
DOI : 10.1198/1061860043029

A. Gelman and X. Meng, Simulating normalizing constants: from importance sampling to bridge sampling to path sampling, Statistical Science, vol.13, issue.2, pp.163-185, 1998.
DOI : 10.1214/ss/1028905934

O. Häggström, Finite Markov Chains and Algorithmic Applications, volume 52 of Student Texts, 2002.

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2001.

J. Heikkinen and H. Hogmander, Fully Bayesian Approach to Image Restoration with an Application in Biogeography, Applied Statistics, vol.43, issue.4, pp.569-582, 1994.
DOI : 10.2307/2986258

J. A. Hoeting, D. Madigan, A. Raftery, and C. Volinsky, Bayesian model averaging: A tutorial (with discussion), Statistical Science, vol.14, issue.4, pp.382-417, 1999.

C. C. Holmes and N. M. Adams, A probabilistic nearest neighbour method for statistical pattern recognition, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.56, issue.2, pp.295-306, 2002.
DOI : 10.1111/1467-9868.00338

C. C. Holmes and N. M. Adams, Likelihood inference in nearest-neighbour classification models, Biometrika, vol.90, issue.1, pp.99-112, 2003.
DOI : 10.1093/biomet/90.1.99

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.137.6366

W. Kendall and J. Møller, Perfect simulation using dominating processes on ordered spaces, with application to locally stable point processes, Advances in Applied Probability, vol.39, issue.03, pp.844-865, 2000.
DOI : 10.1239/aap/1029954267

J. Manocha and M. Girolami, An empirical analysis of the probabilistic K-nearest neighbour classifier, Pattern Recognition Letters, vol.28, issue.13, pp.1818-1824, 2007.
DOI : 10.1016/j.patrec.2007.05.018

G. J. Mclachlan, Discriminant Analysis and Statistical Pattern Recognition, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics, 1992.
DOI : 10.1002/0471725293

J. Møller, Spatial Statistics and Computational Methods, Lecture Notes in Statistics, vol.173, 2003.
DOI : 10.1007/978-0-387-21811-3

J. Møller, A. Pettitt, R. Reeves, and K. Berthelsen, An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants, Biometrika, vol.93, issue.2, pp.451-458, 2006.
DOI : 10.1093/biomet/93.2.451

J. Møller and R. Waagepetersen, Statistical Inference and Simulation for Spatial Point Processes, 2003.
DOI : 10.1201/9780203496930

Y. Ogata, A Monte Carlo method for high dimensional integration, Numerische Mathematik, vol.28, issue.2, pp.137-157, 1989.
DOI : 10.1007/BF01406511

J. Propp and D. Wilson, Coupling from the past: a user's guide, Microsurveys in discrete probability, pp.181-192, 1997.

B. D. Ripley, Neural networks and related methods for classification (with discussion), J. Roy. Statist. Soc. Ser. B, vol.56, issue.3, pp.409-456, 1994.

B. D. Ripley, Pattern Recognition and Neural Networks, 1996.
DOI : 10.1017/CBO9780511812651

C. Robert, The Bayesian Choice, 2001.
DOI : 10.1007/978-1-4757-4314-2

C. P. Robert and G. Casella, Monte Carlo Statistical Methods, 2004.

T. Zhang and B. Yu, Boosting with early stopping: Convergence and consistency, The Annals of Statistics, vol.33, issue.4, pp.1538-1579, 2005.
DOI : 10.1214/009053605000000255

I. Unité-de-recherche, . Lorraine, . Loria, and . Technopôle-de-nancy, Brabois -Campus scientifique 615, rue du Jardin Botanique -BP 101 -54602 Villers-lès-Nancy Cedex (France) Unité de recherche INRIA Rennes : IRISA, Campus universitaire de Beaulieu -35042 Rennes Cedex (France) Unité de recherche INRIA Rhône-Alpes : 655, avenue de l'Europe -38334 Montbonnot Saint-Ismier (France) Unité de recherche INRIA Rocquencourt, Domaine de Voluceau -Rocquencourt -BP 105 -78153 Le Chesnay Cedex (France) Unité de recherche INRIA, pp.93-06902, 2004.

I. De-voluceau-rocquencourt, BP 105 -78153 Le Chesnay Cedex (France) http://www.inria.fr ISSN, pp.249-6399