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WCluster (version 1.3.0)

Clustering and PCA with Weights, and Data Nuggets Clustering

Description

K-means clustering, hierarchical clustering, and PCA with observational weights and/or variable weights. It also includes the corresponding functions for data nuggets which serve as representative samples of large datasets. Cherasia et al., (2022) . Amaratunga et al., (2009) .

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Version

Install

install.packages('WCluster')

Monthly Downloads

277

Version

1.3.0

License

GPL-2

Maintainer

Rituparna Dey

Last Published

March 17th, 2025

Functions in WCluster (1.3.0)

wss

Sums of squares of residuals for observations with weights
wwcss

Weighted Within Cluster Sum of Squares
DNcluster.predict

Predict the closest clusters for a new dataset based on clusters of data nuggets.
DN.Wkmeans

K-means Clustering for data nuggets
cluster.predict

Predict the clusters for a new dataset.
WCluster-package

Clustering and PCA with Observational Weights and/or Variable Weights, and Data Nuggets Clustering
distw

Distance between clusters based on Ward's method for observations with weights
DN.Wpca

Weighted PCA for data nuggets
Wkmeans

K-means Clustering with observational weights
Wpca

Weighted PCA
DN.Whclust

Hierarchical Clustering for data nuggets
Whclust

Hierarchical Clustering with observational weights
wmean

Cluster Centers for observations with weights