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HCV  

Hierarchical Clustering from Vertex-Links
View on CRAN: Click here


Download and install HCV package within the R console
Install from CRAN:
install.packages("HCV")

Install from Github:
library("remotes")
install_github("cran/HCV")

Install by package version:
library("remotes")
install_version("HCV", "1.2.0")



Attach the package and use:
library("HCV")
Maintained by
ShengLi Tzeng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-27
Latest Update:
Description:
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) . 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.
How to cite:
ShengLi Tzeng (2022). HCV: Hierarchical Clustering from Vertex-Links. R package version 1.2.0, https://cran.r-project.org/web/packages/HCV. Accessed 25 Oct. 2026.
Previous versions and publish date:
1.1.0 (2022-01-27 09:50), 1.2.0 (2022-02-22 15:10), (2026-07-09 08:06)
Other packages that cited HCV R package
View HCV citation profile
Other R packages that HCV depends, imports, suggests or enhances
Functions, R codes and Examples using the HCV R package
Some associated functions: HCV . getCluster . plotMap . synthetic_data . tessellation_adjacency_matrix . 
Some associated R codes: HCV.R .  Full HCV package functions and examples
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