Abstract class for defining estimated longitudinal cluster models.
An extending class must implement the following methods to ensure basic functionality:
predict.lcModelExt: Used to obtain the fitted cluster trajectories and trajectories.
postprob(lcModelExt): The posterior probability matrix is used to determine the cluster assignments of the trajectories.
For predicting the posterior probability for unseen data, the predictPostprob() should be implemented.
methodThe lcMethod-class object specifying the arguments under which the model was fitted.
callThe call that was used to create this lcModel object. Typically, this is the call to latrend() or any of the other fitting functions.
modelAn arbitrary underlying model representation.
dataA data.frame object, or an expression to resolves to the data.frame object.
dateThe date-time when the model estimation was initiated.
idThe name of the trajectory identifier column.
timeThe name of the time variable.
responseThe name of the response variable.
labelThe label assigned to this model.
idsThe trajectory identifier values the model was fitted on.
timesThe exact times on which the model has been trained
clusterNamesThe names of the clusters.
estimationTimeThe time, in seconds, that it took to fit the model.
tagAn arbitrary user-specified data structure. This slot may be accessed and updated directly.
Other lcModel functions:
clusterNames(),
clusterProportions(),
clusterSizes(),
clusterTrajectories(),
coef.lcModel(),
converged(),
deviance.lcModel(),
df.residual.lcModel(),
estimationTime(),
externalMetric(),
fitted.lcModel(),
fittedTrajectories(),
getCall.lcModel(),
getLcMethod(),
ids(),
metric(),
model.frame.lcModel(),
nClusters(),
nIds(),
nobs.lcModel(),
plot-lcModel-method,
plotClusterTrajectories(),
plotFittedTrajectories(),
postprob(),
predict.lcModel(),
predictAssignments(),
predictForCluster(),
predictPostprob(),
qqPlot(),
residuals.lcModel(),
sigma.lcModel(),
strip(),
time.lcModel(),
trajectoryAssignments()