TRAC-class: TRAC: Creating a Markov Model from a Regular Clustering

In rEMM: Extensible Markov Model for Modelling Temporal Relationships Between Clusters

TRAC: Creating a Markov Model from a Regular Clustering

Description

Create an Markov model from a regular clustering (k-means or PAM) of sequence data.

Usage

TRAC(x, data = NULL, centers = NULL, measure = "euclidean")

Arguments

x	a clustering object (result of kmeans or PAM), a data set (a data matrix), or a vector with (integer) cluster assignments.
data	the data used for clustering (only used if x is a cluster assignment vector).
centers	if x is a cluster assignment vector, then a data.frame or matrix with the cluster centers needs to be supplies. Otherwise, centers is ignored.
measure	used distance measure.

Details

The order is inferred from the order in the original data set.

Value

A EMM object representing the clustering of sequence data.

Examples

data("EMMsim")

## using kmeans
cl <- kmeans(EMMsim_train, 10)
emm <- TRAC(cl)
emm
plot(emm, method = "MDS")

## using a cluster assignment vector (taken from the k-means clustering above)
x <- cl$cluster
emm <- TRAC(x, data = EMMsim_train)
emm
plot(emm, method = "MDS")

rEMM documentation built on May 29, 2024, 4:35 a.m.