sepIndex {clusterGeneration} | R Documentation |
Measure the magnitude of the gap or sparse area between a pair of clusters (or cluster distributions) along the specified projection direction.
sepIndexTheory(projDir, mu1, Sigma1, mu2, Sigma2, alpha=0.05, eps=1.0e-10, quiet=TRUE) sepIndexData(projDir, y1, y2, alpha=0.05, eps=1.0e-10, quiet=TRUE)
projDir |
Projection direction. |
mu1 |
Mean vector of cluster 1. |
Sigma1 |
Covariance matrix of cluster 1. |
mu2 |
Mean vector of cluster 2. |
Sigma2 |
Covariance matrix of cluster 2. |
y1 |
Data matrix of cluster 1. Rows correspond to observations. Columns correspond to variables. |
y2 |
Data matrix of cluster 2. Rows correspond to observations. Columns correspond to variables. |
alpha |
Tuning parameter reflecting the percentage in the two
tails of a projected cluster that might be outlying.
We set |
eps |
Convergence threshold. A small positive number to check if a quantitiy q
is equal to zero. If |q|< |
quiet |
A flag to switch on/off the outputs of intermediate results and/or possible warning messages. The default value is |
The value of the separation index defined in Qiu and Joe (2006).
Weiliang Qiu stwxq@channing.harvard.edu
Harry Joe harry@stat.ubc.ca
Qiu, W.-L. and Joe, H. (2006) Separation Index and Partial Membership for Clustering. Computational Statistics and Data Analysis, 50, 585–603.
n1<-50 mu1<-c(0,0) Sigma1<-matrix(c(2,1,1,5),2,2) n2<-100 mu2<-c(10,0) Sigma2<-matrix(c(5,-1,-1,2),2,2) projDir<-c(1, 0) sepIndexTheory(projDir, mu1, Sigma1, mu2, Sigma2) library(MASS) y1<-mvrnorm(n1, mu1, Sigma1) y2<-mvrnorm(n2, mu2, Sigma2) sepIndexData(projDir, y1, y2)