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funIHC  

Functional Iterative Hierarchical Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("funIHC", "0.1.0")



Attach the package and use:
library("funIHC")
Maintained by
Catherine Higgins
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-09
Latest Update: 2026-01-09
Description:
Functional clustering aims to group curves exhibiting similar temporal behaviour and to obtain representative curves summarising the typical dynamics within each cluster. A key challenge in this setting is class imbalance, where some clusters contain substantially more curves than others, which can adversely affect clustering performance. While class imbalance has been extensively studied in supervised classification, it has received comparatively little attention in unsupervised clustering. This package implements functional iterative hierarchical clustering ('funIHC'), an adaptation of the iterative hierarchical clustering method originally developed for multivariate data, to the functional data setting. For further details, please see Higgins and Carey (2024) <doi:10.1007/s11634-024-00611-8>.
How to cite:
Catherine Higgins (2026). funIHC: Functional Iterative Hierarchical Clustering. R package version 0.1.0, https://cran.r-project.org/web/packages/funIHC. Accessed 17 Jul. 2026.
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Complete documentation for funIHC
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Full funIHC package functions and examples
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