S. Bellec, D. Hémon, and J. Clavel, Answering Cluster Investigation Requests: The Value of Simple Simulations and Statistical Tools, European Journal of Epidemiology, vol.33, issue.7, pp.663-671, 2005.
DOI : 10.1007/s10654-005-7924-x

URL : https://hal.archives-ouvertes.fr/inserm-00085388

L. Huang, L. Pickle, and B. Das, Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases, Statistics in Medicine, vol.42, issue.4, pp.5111-5142, 2008.
DOI : 10.1002/sim.3342

X. Li, J. Wang, W. Yang, Z. Li, and S. Lai, A spatial scan statistic for multiple clusters, Mathematical Biosciences, vol.233, issue.2, pp.135-142, 2011.
DOI : 10.1016/j.mbs.2011.07.004

G. Aamodt, S. Samuelsen, and A. Skrondal, A simulation study of three methods for detecting disease clusters, International journal of health, p.16608532, 2006.

G. Jacquez, Cluster morphology analysis. Spatial and spatio-temporal epidemiology 1: 19?29, p.20234799, 2009.

S. Goujon-bellec, C. Demoury, A. Guyot-goubin, D. Hémon, and J. Clavel, Detection of clusters of a rare disease over a large territory: performance of cluster detection methods, International Journal of Health Geographics, vol.10, issue.1, pp.53-63, 2011.
DOI : 10.1002/sim.2418

URL : https://hal.archives-ouvertes.fr/inserm-00637064

L. Waller, E. Hill, and R. Rudd, The geography of power: statistical performance of tests of clusters and clustering in heterogeneous populations, Statistics in Medicine, vol.55, issue.5, pp.853-865, 2006.
DOI : 10.1002/sim.2418

T. Zhang, Z. Zhang, and G. Lin, Spatial scan statistics with overdispersion, Statistics in Medicine, vol.21, issue.8, pp.762-774, 2012.
DOI : 10.1002/sim.4404

A. Guttmann, L. Ouchchane, X. Li, I. Perthus, J. Gaudart et al., Performance map of a cluster detection test using extended power, International Journal of Health Geographics, vol.12, issue.1, pp.47-57, 2013.
DOI : 10.1016/j.sste.2012.04.004

URL : https://hal.archives-ouvertes.fr/inserm-00903889

K. Takahashi and T. Tango, An extended power of cluster detection tests, Statistics in Medicine, vol.42, issue.5, pp.841-852, 2006.
DOI : 10.1002/sim.2419

T. Tanimoto, IBM internal report, nov, 1957.

D. Rogers and T. Tanimoto, A Computer Program for Classifying Plants, Science, vol.132, issue.3434, pp.1115-1118, 1960.
DOI : 10.1126/science.132.3434.1115

L. Kara and T. Stahovich, An image-based, trainable symbol recognizer for hand-drawn sketches, Computers & Graphics, vol.29, issue.4, pp.501-517, 2005.
DOI : 10.1016/j.cag.2005.05.004

R. Duda, P. Hart, and D. Stork, Pattern classification, 2012.

S. Chatzichristofis and Y. Boutalis, CEDD: Color and Edge Directivity Descriptor: A Compact Descriptor for Image Indexing and Retrieval, pp.312-322, 2008.
DOI : 10.1007/978-3-540-79547-6_30

P. Willett, Similarity-based approaches to virtual screening, Biochemical Society Transactions, vol.31, issue.3, pp.603-606, 2003.
DOI : 10.1042/bst0310603

E. Martin, J. Blaney, M. Siani, D. Spellmeyer, A. Wong et al., Measuring Diversity: Experimental Design of Combinatorial Libraries for Drug Discovery, Journal of Medicinal Chemistry, vol.38, issue.9, pp.1431-1436, 1995.
DOI : 10.1021/jm00009a003

A. Burton, D. Altman, P. Royston, and R. Holder, The design of simulation studies in medical statistics, Statistics in Medicine, vol.23, issue.24, pp.4279-4292, 2006.
DOI : 10.1002/sim.2673

J. Ahrens and U. Dieter, Computer Generation of Poisson Deviates from Modified Normal Distributions, ACM Transactions on Mathematical Software, vol.8, issue.2, pp.163-179, 1982.
DOI : 10.1145/355993.355997

M. Matsumoto and T. Nishimura, Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator, ACM Transactions on Modeling and Computer Simulation, vol.8, issue.1, pp.3-30, 1998.
DOI : 10.1145/272991.272995

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.1141

C. Chen, A. Kim, M. Ross, J. Wakefield, and E. Venkatraman, SpatialEpi: Performs various spatial epidemiological analyses, 2013.

R. Analytics and S. Weston, foreach: Foreach looping construct for R. URL http:// CRAN.R-project.org/package = foreach, 2013.

M. Kulldorff and N. Nagarwalla, Spatial disease clusters: Detection and inference, Statistics in Medicine, vol.132, issue.8, pp.799-810, 1995.
DOI : 10.1002/sim.4780140809

M. Kulldorff, A spatial scan statistic, Communications in Statistics - Theory and Methods, vol.75, issue.6, pp.1481-1496, 1997.
DOI : 10.1093/biomet/74.3.631

S. Ribeiro and M. Costa, Optimal selection of the spatial scan parameters for cluster detection: A simulation study, Spatial and Spatio-temporal Epidemiology, vol.3, issue.2, pp.107-120, 2012.
DOI : 10.1016/j.sste.2012.04.004

A. Ozonoff, C. Jeffery, J. Manjourides, L. White, and M. Pagano, Effect of spatial resolution on cluster detection: a simulation study, International Journal of Health Geographics, vol.6, issue.1, pp.52-18042281, 2007.
DOI : 10.1186/1476-072X-6-52

M. Kulldorff, T. Tango, and P. Park, Power comparisons for disease clustering tests, Computational Statistics & Data Analysis, vol.42, issue.4, pp.665-684, 2003.
DOI : 10.1016/S0167-9473(02)00160-3