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kmlcov (version 1.0.1)

Clustering longitudinal data using the likelihood as a metric of distance

Description

'kmlcov' Cluster longitudinal data using the likelihood as a metric of distance. The generalised linear model allow the user to introduce covariates with different level effects (2 levels).

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Version

Install

install.packages('kmlcov')

Monthly Downloads

10

Version

1.0.1

License

GPL-2

Maintainer

Mamoun O Benghezal

Last Published

August 21st, 2013

Functions in kmlcov (1.0.1)

affect_rand

Affect randomly the individuals to the clusters
rwFormula

Rewrite the formula with all the covariates
GlmCluster-class

Class GlmCluster
kmlcov-package

Clustering longitudinal data using the likelihood as a metric of distance
log_lik

Calculate the log-likelihood
artifdata

Artificial data
majIndica

Calculate an indicator vector
Converge-class

Class "Converge"
GlmCluster-methods

Plot the main trajectories
glmClust

Clustering longitudinal data
KmlCovList-class

Class KmlCovList
predict_clust

Creates a character string expression to calculate the predicted values
addIndic

Create the new formula with the indicator covariates
getNomCoef

Get the name of the coefficients in the 'glm' object according to the current cluster
plot-methods

Plot the main trajectories
seperateFormula

Separate the covariates in a formula
which_best

Seek the best partitions
Converge-methods

Method for function show
kmlCov

Clustering longitudinal data from different starting conditions