`GlmCluster`

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

`GlmCluster`

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

`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.

plot,GlmCluster-methodplot Display the main trajectories.

Meant to be used internally.

Classes: `Converge`

.

Plot: `plot(GlmCluster)`

.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

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