A contingency table approach based on nearest neighbour relations for testing self and mixed correspondence
Copyright policy )A contingency table approach based on nearest neighbour relations for testing self and mixed correspondence
Nearest neighbour methods are employed for drawing inferences about spatial patterns of points from two or more classes. We introduce a new pattern called correspondence which is motivated by (spatial) niche/habitat specificity and segregation, and define an associated contingency table called a correspondence contingency table, and examine the relation of correspondence with the motivating patterns (namely, segregation and niche specificity). We propose tests based on the correspondence contingency table for testing self and mixed correspondence and determine the appropriate null hypotheses and the underlying conditions appropriate for these tests. We compare finite sample performance of the tests in terms of empirical size and power by extensive Monte Carlo simulations and illustrate the methods on two artificial data sets and one real-life ecological data set.
Peer Reviewed
Inference from spatial processes, Habitat/niche specificity, independence, Classificació AMS::62 Statistics::62H Multivariate analysis, Association, complete spatial randomness, habitat/niche specificity, independence, random labelling, segregation, Classificació AMS::62 Statistics::62P Applications, :62 Statistics::62G Nonparametric inference [Classificació AMS], Association, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Classificació AMS::62 Statistics::62M Inference from stochastic processes, random labelling, :62 Statistics::62M Inference from stochastic processes [Classificació AMS], Random labelling, Complete spatial randomness, association, Segregation, :62 Statistics::62P Applications [Classificació AMS], :62 Statistics::62H Multivariate analysis [Classificació AMS], Contingency tables, Independence, complete spatial randomness, habitat/niche specificity, segregation, :Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], 62M30, 62G10, 62H11, 62P12, 62H30, Classificació AMS::62 Statistics::62G Nonparametric inference, Applications of statistics to environmental and related topics
Inference from spatial processes, Habitat/niche specificity, independence, Classificació AMS::62 Statistics::62H Multivariate analysis, Association, complete spatial randomness, habitat/niche specificity, independence, random labelling, segregation, Classificació AMS::62 Statistics::62P Applications, :62 Statistics::62G Nonparametric inference [Classificació AMS], Association, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Classificació AMS::62 Statistics::62M Inference from stochastic processes, random labelling, :62 Statistics::62M Inference from stochastic processes [Classificació AMS], Random labelling, Complete spatial randomness, association, Segregation, :62 Statistics::62P Applications [Classificació AMS], :62 Statistics::62H Multivariate analysis [Classificació AMS], Contingency tables, Independence, complete spatial randomness, habitat/niche specificity, segregation, :Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], 62M30, 62G10, 62H11, 62P12, 62H30, Classificació AMS::62 Statistics::62G Nonparametric inference, Applications of statistics to environmental and related topics
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