Specialized agglomerations with Lattice data: Model and detection
(2015) Spatial Statistics — Vol. 11, p. 113-131 (2015)
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- Abstract
- This paper develops new statistical and computational methods for the automatic detection of spatial clusters displaying an over- or under- relative specialization spatial pattern. A probability model is used to provide a basis for a space partition into clusters representing homogeneous portions of space as far as the probability of locating a primary unit is concerned. A cluster made of contiguous regions is called an agglomeration. A greedy algorithm detects specialized agglomerations through a model selection criteria. A random permutation test evaluates whether the contiguity property is significant. Finally this algorithm is run on Argentinean data. Evaluating the proposed methodology concludes the paper.
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Haedo, C., & Mouchart, M. (2015). Specialized agglomerations with Lattice data: Model and detection. Spatial Statistics, 11, 113-131. https://doi.org/10.1016/j.spasta.2014.11.003 (Original work published 2015)