ClustGeo: an R package for hierarchical clustering with spatial constraints

• Published in: Computational statistics Vol. 33; no. 4; pp. 1799 - 1822
• Main Authors: Chavent, Marie, Kuentz-Simonet, Vanessa, Labenne, Amaury, Saracco, Jérôme
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2018; Springer Nature B.V; Springer Verlag
• Subjects: Clustering; Computation; Criteria; Economic Theory/Quantitative Economics/Mathematical Methods; Homogeneity; Mathematical analysis; Mathematics and Statistics; Original Paper; Other Statistics; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Statistics; Non-Euclidean dissimilarities; Soft contiguity constraints; Pseudo-inertia; Ward-like hierarchical clustering; Geographical distances

In this paper, we propose a Ward-like hierarchical clustering algorithm including spatial/geographical constraints. Two dissimilarity matrices D 0 and D 1 are inputted, along with a mixing parameter α ∈ [ 0 , 1 ] . The dissimilarities can be non-Euclidean and the weights of the observations can be n...