Clustering longitudinal data using the likelihood as a metric of distance

Documentation for package ‘kmlcov’ version 1.0.1

kmlcov-package	Clustering longitudinal data using the likelihood as a metric of distance
addIndic	Create the new formula with the indicator covariates
affect_rand	Affect randomly the individuals to the clusters
alias	Class '"Converge"'
artifdata	Artificial data
Converge-class	Class '"Converge"'
getNomCoef	Get the name of the coefficients in the 'glm' object according to the current cluster
glmClust	Clustering longitudinal data
GlmCluster	Class 'GlmCluster'
GlmCluster-class	Class 'GlmCluster'
kmlCov	Clustering longitudinal data from different starting conditions
kmlcov	Clustering longitudinal data using the likelihood as a metric of distance
KmlCovList	Class 'KmlCovList'
KmlCovList-class	Class 'KmlCovList'
log_lik	Calculate the log-likelihood
majIndica	Calculate an indicator vector
plot-method	Plot the main trajectories
plot-method	Plot the main trajectories
predict_clust	Creates a character string expression to calculate the predicted values
rwFormula	Rewrite the formula with all the covariates
seperateFormula	Separate the covariates in a formula
show-method	Method for function 'show'
which_best	Seek the best partitions