Predict the cluster assignments for new trajectories — predictAssignments • latrend

Predict the most likely cluster membership for each trajectory in the given data.

predictAssignments(object, newdata = NULL, ...)

# S4 method for lcModel
predictAssignments(object, newdata = NULL, strategy = which.max, ...)

Arguments

object: The model.
newdata: A data.frame of trajectory data for which to compute trajectory assignments.
...: Not used.
strategy: A function returning the cluster index based on the given vector of membership probabilities. By default (strategy = which.max), trajectories are assigned to the most likely cluster.

Value

A factor of length nrow(newdata) that indicates the assigned cluster per trajectory per observation.

Details

The default implementation uses predictPostprob to determine the cluster membership.

See also

predictPostprob predict.lcModel

Other lcModel functions: clusterNames(), clusterProportions(), clusterSizes(), clusterTrajectories(), coef.lcModel(), converged(), deviance.lcModel(), df.residual.lcModel(), estimationTime(), externalMetric(), fitted.lcModel(), fittedTrajectories(), getCall.lcModel(), getLcMethod(), ids(), lcModel-class, metric(), model.frame.lcModel(), nClusters(), nIds(), nobs.lcModel(), plot-lcModel-method, plotClusterTrajectories(), plotFittedTrajectories(), postprob(), predict.lcModel(), predictForCluster(), predictPostprob(), qqPlot(), residuals.lcModel(), sigma.lcModel(), strip(), time.lcModel(), trajectoryAssignments()

Examples

if (FALSE) {
data(latrendData)
if (require("kml")) {
  model <- latrend(method = lcMethodKML("Y", id = "Id", time = "Time"), latrendData)
  predictAssignments(model, newdata = data.frame(Id = 999, Y = 0, Time = 0))
}
}