HCV: Hierarchical Clustering from Vertex-Links

Hierarchical clustering for spatial data, which requires clustering results not only homogeneous in non-geographical features among samples but also geographically close to each other within a cluster. It modified typically used hierarchical agglomerative clustering algorithms for introducing the spatial homogeneity, by considering geographical locations as vertices and converting spatial adjacency into whether a shared edge exists between a pair of vertices (Tzeng & Hsu, 2022) <arXiv:2201.08302>. The constraints of the vertex links automatically enforce the spatial contiguity property at each step of iterations. In addition, methods to find an appropriate number of clusters and to report cluster members are also provided.

Getting started

Package details

AuthorShengLi Tzeng [cre, aut], Hao-Yun Hsu [aut]
MaintainerShengLi Tzeng <slt.cmu@gmail.com>
LicenseLGPL-3
Version1.2.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("HCV")

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HCV documentation built on March 18, 2022, 6:01 p.m.