GlmCluster-class: Class 'GlmCluster'

In kmlcov: Clustering longitudinal data using the likelihood as a metric of distance

Description

GlmCluster contains all relevant information about the trajectories obtained and the affectation to the clusters.

Objects from the Class

GlmCluster is used inside glmClust and contain all the information to plot and print the main trajectories.

Slots

formula:

Object of class formula.

nClust:

The number of clusters.

ident:

Name of the 'identity' column in the data.

timeVar:

Name of the 'time' column in the data.

time:

Numeric Vector of the time.

effectVar:

Name of a variable with cluster effect or not.

effect:

A variable effect, can be a level cluster effect or not.

model.glm:

A glm object.

timeParametric:

Object of class logical.

partition:

Vector of integer containing the affectation of the individuals to the clusters.

partition.long:

Same as partition but with repeated measures corresponding to the number of observations for each individual

proportions:

Proportions of individuals (trajectories) affected in each cluster

criteria:

A matrix which contains the values of the 'log-likelihood', the 'AIC' (Akaike Information Criterion) and 'BIC' (bayesian information criterion).

converge:

An object of class Converge.

nIter:

Number of iterations of the algorithm.

for_ggplot:

A data.frame containing the time and the typical trajectories.

Methods

plot,GlmCluster-methodplot Display the main trajectories.

Note

Meant to be used internally.

See Also

Classes: Converge.
Plot: plot(GlmCluster).

kmlcov documentation built on May 2, 2019, 11:38 a.m.