Spatial cluster detection using nearest neighbor distance
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Ashton, 2000, Spatial patterns in the distribution of tropical tree species, Science, 288, 1414, 10.1126/science.288.5470.1414
Baddeley, 2005, Spatstat: an r package for analyzing spatial point patterns, Spat. Stat., 12, 103
Baker, 1975, Measuring the power of hierarchical cluster analysis, Psychol. Bull., 70, 31
Calinski, 1974, An examination of procedures for determining the number of clusters in a data set, Commun. Stat., 3, 1
Charrad, 2014, Nbclust: An r package for determining the relevant number of clusters in a data set, Spat. Stat., 61
Collinet, 1997
Cressie, 1993
Daley, 1988
Dalling, 2007, Soil nutrients influence spatial distributions of tropical tree species, Proc. Natl. Acad. Sci. USA, 104, 864, 10.1073/pnas.0604666104
Demattei, 2007, Arbitrarily shaped multiple spatial cluster detection for case event data, Comput. Statist. Data Anal., 51, 3931, 10.1016/j.csda.2006.03.011
Dessard, H., N Picard, N., Collinet-Vautier, F., 2004. Spatial patterns of the most abundant tree species. In: S. Gourlet-Fleury, J. M. G.. O. L., (Eds.), Ecology and management of a neotropical rainforest. Lessons drawn from Paracou, a long-term experimental research site in French Guiana, pp. 177–190.
Diggle, 1983
Duczmal, 2004, A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters, Comput. Statist. Data Anal., 45, 269, 10.1016/S0167-9473(02)00302-X
Duda, 1973
F~Dormann, 2007, Methods to account for spatial autocorrelation in the analysis of species distributional data: a review, Ecography, 30, 609, 10.1111/j.2007.0906-7590.05171.x
Gourlet-Fleury, S., Ferry, B., Molino, J.F., Petronelli, P., 2004. Paracou experimental plots: key features. In: S. Gourlet-Fleury, J. M. G.. O. L., (Eds.), Ecology and management of a neotropical rainforest. Lessons drawn from Paracou, a long-term experimental research site in French Guiana, pp. 17–34.
Halkidi, 2001, Clustering validity assessment: finding the optimal partitioning of a data set, 187
Halkidi, 2000, Quality scheme assessment in the clustering process, vol. 1910, 265
Hartigan, 1975
Hubert, 1976, A general statistical framework for assessing categorical clustering in free recall, Psychol. Bull., 83, 1072, 10.1037/0033-2909.83.6.1072
Krzanowski, 1988, A criterion for determining the number of groups in a data set using sum-of-squares clustering, Biometrics, 44, 23, 10.2307/2531893
Kulldorff, 1997, A spatial scan statistic, Commun. Stat. Theory, 26, 1481, 10.1080/03610929708831995
Kulldorff, M., and Information Management Services, I. (2009). Satscantm v9.1: Software for the spatial and space–time scan statistics. http://www.satscan.org/.
Kulldorff, 1995, Spatial disease clusters: detection and inference, Stat. Med., 14, 799, 10.1002/sim.4780140809
Loubry, 1993, Les paradoxes de l’angélique (Dicorynia guianensis amshoff): dissémination et parasitisme des graines avant dispersion chez un arbre anémochore de forêt guyanaise, Rev. Écol. (Terre et Vie), 48, 353, 10.3406/revec.1993.2115
Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K., 2014. cluster: Cluster Analysis Basics and Extensions. R package version 1.15.3—For new features, see the ’Changelog’ file (in the package source).
Milligan, 1985, An examination of procedures for determining the number of clusters in a data set, Psychometrika, 50, 159, 10.1007/BF02294245
Murray, 2014, Spatially significant cluster detection, Spat. Stat., 10, 103, 10.1016/j.spasta.2014.03.001
Ord, 1995, Local spatial autocorrelation statistics: distributional issues and an application, Geogr. ann, 27, 286, 10.1111/j.1538-4632.1995.tb00912.x
Patil, 2004, Upper level set scan statistic for detecting arbitrarily shaped hotspots, Environ. Ecol. Stat., 11, 183, 10.1023/B:EEST.0000027208.48919.7e
Ripley, 1988
Rousseeuw, 1987, Silhouettes: a graphical aid to the interpretation and validation of cluster analysis, J. Comput. Appl. Math., 20, 53, 10.1016/0377-0427(87)90125-7
Stojanova, 2013, Dealing with spatial autocorrelation when learning predictive clustering trees, Ecol. Inform., 13, 22, 10.1016/j.ecoinf.2012.10.006
Stoyan, 1995
Stoyan, 1994
Tango, 2005, A flexibly shaped spatial scan statistic for detecting clusters, Int. J. Health Geogr., 4, 10.1186/1476-072X-4-11
Tibshirani, 2001, Estimating the number of data clusters via the gap statistic, J. Roy. Stat. Soc. B, 63, 411, 10.1111/1467-9868.00293
Traissac, 2014, Birth and life of tree aggregates in tropical forest: hypotheses on population dynamics of an aggregated shade-tolerant species, J. Veg. Sci., 25, 491, 10.1111/jvs.12080
van Lieshout, 2012, On estimation of the intensity function of a point process, Methodol. Comput. Appl. Probab., 14, 567, 10.1007/s11009-011-9244-9
Waagepetersen, 2007, An estimating function approach to inference for inhomogeneous neyman–scott processes, Biometrics, 63, 252, 10.1111/j.1541-0420.2006.00667.x
West, 2001