predictPostprob: lcModel posterior probability prediction

In latrend: A Framework for Clustering Longitudinal Data

lcModel posterior probability prediction

Description

Returns the observation-specific posterior probabilities for the given data. The default implementation returns a uniform probability matrix.

Usage

## S4 method for signature 'lcModel'
predictPostprob(object, newdata = NULL, ...)

Arguments

object	The lcModel to predict the posterior probabilities with.
newdata	Optional data frame for which to compute the posterior probability. If omitted, the model training data is used.
...	Additional arguments.

Value

A N-by-K matrix indicating the posterior probability per trajectory per measurement on each row, for each cluster (the columns). Here, N = nrow(newdata) and K = nClusters(object).

Implementation

Classes extending lcModel should override this method to enable posterior probability predictions for new data.

setMethod("predictPostprob", "lcModelExt", function(object, newdata = NULL, ...) {
  # return observation-specific posterior probability matrix
})

See Also

Other lcModel functions: clusterNames(), clusterProportions(), clusterSizes(), clusterTrajectories(), coef.lcModel(), converged(), deviance.lcModel(), df.residual.lcModel(), estimationTime(), externalMetric,lcModel,lcModel-method, 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(), qqPlot(), residuals.lcModel(), sigma.lcModel(), strip(), time.lcModel(), trajectoryAssignments()

latrend documentation built on March 31, 2023, 5:45 p.m.