wmean | R Documentation |
This function computes the weighted cluster centers for a set of cluster assignments provided to a dataset with observational weights.
wmean(x,cl,w)
x |
A data matrix (data frame, data table, matrix, etc.) containing only entries of class numeric. |
cl |
Vector of length nrow(x) of cluster assignments for each observation in the dataset, indicating the cluster to which each observation is allocated. Must be of class integer. |
w |
Vector of length nrow(x) of weights for each observation in the dataset. Must be of class numeric or integer. If NULL, the default value is a vector of 1 with length nrow(x), i.e., weights equal 1 for all observations. |
In this function, the function weighted.mean
in the stats
package is used to calculate the cluster centers for each cluster with observational weights.
A matrix of cluster centres. Each column is a weighted center for one cluster.
Javier Cabrera, Yajie Duan, Ge Cheng
Cherasia, K. E., Cabrera, J., Fernholz, L. T., & Fernholz, R. (2022). Data Nuggets in Supervised Learning. In Robust and Multivariate Statistical Methods: Festschrift in Honor of David E. Tyler (pp. 429-449). Cham: Springer International Publishing.
Beavers, T., Cheng, G., Duan, Y., Cabrera, J., Lubomirski, M., Amaratunga, D., Teigler, J. (2023). Data Nuggets: A Method for Reducing Big Data While Preserving Data Structure (Submitted for Publication)
Wkmeans
require(cluster)
# The Ruspini data set from the package "cluster""
x = as.matrix(ruspini)
# assign random weights to observations
w = sample(1:10,nrow(x),replace = TRUE)
# assign random clusters to observations
cl = sample(1:3,nrow(x),replace = TRUE)
#output the weighted cluster centers for each cluster under the random cluster assignments
wmean(x, cl, w)
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