trajectoryAssignments {latrend}

Get the cluster membership of each trajectory

Description

Get the cluster membership of each trajectory associated with the given model.

For lcModel: Classify the fitted trajectories based on the posterior probabilities computed by postprob(), according to a given classification strategy.

By default, trajectories are assigned based on the highest posterior probability using which.max(). In cases where identical probabilities are expected between clusters, it is preferable to use which.is.max instead, as this function breaks ties at random. Another strategy to consider is the function which.weight(), which enables weighted sampling of cluster assignments based on the trajectory-specific probabilities.

Usage

trajectoryAssignments(object, ...)

## S4 method for signature 'matrix'
trajectoryAssignments(
  object,
  strategy = which.max,
  clusterNames = colnames(object),
  ...
)

## S4 method for signature 'lcModel'
trajectoryAssignments(object, strategy = which.max, ...)

Arguments

object

The model.

...

Any additional arguments passed to the strategy function.

strategy

A function returning the cluster index based on the given vector of membership probabilities. By default, ids are assigned to the cluster with the highest probability.

clusterNames

Optional ⁠character vector⁠ with the cluster names. If clusterNames = NULL, make.clusterNames() is used.

Details

In case object is a matrix: the posterior probability matrix, with the kth column containing the observation- or trajectory-specific probability for cluster k.

Value

A ⁠factor vector⁠ indicating the cluster membership for each trajectory.

See Also

postprob clusterSizes predictAssignments

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(), predictAssignments(), predictForCluster(), predictPostprob(), qqPlot(), residuals.lcModel(), sigma.lcModel(), strip(), time.lcModel()

Examples

data(latrendData)
method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time")
model <- latrend(method, latrendData)
trajectoryAssignments(model)

# assign trajectories at random using weighted sampling
trajectoryAssignments(model, strategy = which.weight)