compute.cumulative.multiple: Function to compute the empirical cumulative distribution...

In mosclust: Model Order Selection for Clustering

Function to compute the empirical cumulative distribution function (ECDF) of the similarity measures.

Description

The function compute.cumulative.multiple computes the empirical cumulative distribution function (ECDF) of the similarity measures for different number of clusters between clusterings. The function cumulative.values returns the values of the empirical cumulative distribution

Usage

compute.cumulative.multiple(sim.matrix)

cumulative.values(Fun)

Arguments

sim.matrix	a matrix that stores the similarity between pairs of clustering across multiple number of clusters and multiple clusterings. Each row corresponds to a different number of clusters; number of columns equal to the number of subsamples considered for each number of clusters.
Fun	Function of class ecdf that stores the discrete values of the cumulative distribution

Value

Function compute.cumulative.multiple: a list of function of class ecdf.

Function cumulative.values: a list with two elements: the "x" element stores a vector with the values of the random variable for which the cumulative distribution needs to be computed; the "y" element stores a vector with the corresponding values of the cumulative distribution (i.e. y = F(x)).

Author(s)

Giorgio Valentini [e-mail]

See Also

plot_cumulative.multiple

Examples

library("clusterv")
# Data set generation
M <- generate.sample6 (n=20, m=10, dim=1000, d=3, s=0.2);
# generation of multiple similarity measures by resampling
Sr.kmeans.sample6 <- do.similarity.resampling(M, c=10, nsub=20, f=0.8, s=sFM, 
                                      alg.clust.sim=Kmeans.sim.resampling); 
# computation of multiple ecdf (from 2 to 10 clusters)
list.F <- compute.cumulative.multiple(Sr.kmeans.sample6);
# values of the ecdf for 8 clusters 
l <- cumulative.values(list.F[[7]])

mosclust documentation built on June 8, 2025, 11:23 a.m.