Hamada S. Badr [aut, cre], Benjamin F. Zaitchik [aut], Amin K. Dezfuli [aut]
HiClimR package modifies and improves hierarchical clustering in R ('hclust' function in 'stats'
library), for climate regionalization. It adds a new clustering method (called, regional linkage)
to the set of available methods together with several features including regridding, coarsening
spatial resolution, geographic masking, data thresholds, detrending and standardization data
preprocessing, faster correlation function, hybrid hierarchical clustering, and cluster validation.
It is applicable to any correlation-based clustering.

A tool for hierarchical climate regionalization applicable to any correlation-based clustering.
It adds several features and a new clustering method (called, regional linkage) to hierarchical
clustering in R (`hclust` function in `stats` library): regridding, coarsening spatial resolution,
geographic masking, data filtering by thresholds, data preprocessing (detrending, standardization,
and PCA), faster correlation function, hybrid hierarchical clustering, and cluster validation.

A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering.
It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical
clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution,
geographic masking (by continents, regions, or countries), data filtering by mean and/or variance
thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function
with preliminary big data support, hybrid hierarchical clustering, multi-variate clustering (MVC),
cluster validation, and visualization of region maps.

A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering.
It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical
clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution,
geographic masking (by continents, regions, or countries), data filtering by mean and/or variance
thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function
with preliminary big data support, different clustering methods, hybrid hierarchical clustering,
multi-variate clustering (MVC), cluster validation, and visualization of region maps.