latrend (version 1.1.0)

predict.lcModel: lcModel predictions

Description

Predicts the expected trajectory observations at the given time for each cluster.

Usage

# S3 method for lcModel
predict(object, newdata = NULL, what = "mu", ...)

Arguments

object

The lcModel object.

newdata

Optional data.frame for which to compute the model predictions. If omitted, the model training data is used. Cluster trajectory predictions are made when ids are not specified.

what

The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what = 'mb'.

...

Additional arguments.

Value

If newdata specifies the cluster membership; a data.frame of cluster-specific predictions. Otherwise, a list of data.frame of cluster-specific predictions is returned.

Details

Subclasses of lcModel should preferably implement predictForCluster instead of overriding predict.lcModel in order to benefit from standardized error checking and output handling.

See Also

Other model-specific methods: clusterTrajectories(), coef.lcModel(), converged(), deviance.lcModel(), df.residual.lcModel(), fitted.lcModel(), lcModel-class, logLik.lcModel(), model.frame.lcModel(), nobs.lcModel(), postprob(), predictAssignments(), predictForCluster(), predictPostprob(), residuals.lcModel(), sigma.lcModel(), time.lcModel(), trajectories()

Examples

# NOT RUN {
data(latrendData)
model <- latrend(lcMethodLcmmGMM(
   fixed = Y ~ Time, mixture = ~ Time,
   id = "Id", time = "Time"), latrendData)
predFitted <- predict(model) # same result as fitted(model)

# Cluster trajectory of cluster A
predCluster <- predict(model, newdata = data.frame(Cluster = "A", Time = time(model)))

# Prediction for id S1 given cluster A membership
predId <- predict(model, newdata = data.frame(Cluster = "A", Id = "S1", Time = time(model)))

# Prediction matrix for id S1 for all clusters
predIdAll <- predict(model, newdata = data.frame(Id = "S1", Time = time(model)))
# }