Returns the observation-specific posterior probabilities for the given data. The default implementation returns a uniform probability matrix.
# S4 method for lcModel
predictPostprob(object, newdata = NULL, ...)
The lcModel
to predict the posterior probabilities with.
Optional data frame for which to compute the posterior probability. If omitted, the model training data is used.
Additional arguments.
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)
.
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 })
Other model-specific methods:
clusterTrajectories()
,
coef.lcModel()
,
converged()
,
deviance.lcModel()
,
df.residual.lcModel()
,
fitted.lcModel()
,
fittedTrajectories()
,
lcModel-class
,
logLik.lcModel()
,
model.frame.lcModel()
,
nobs.lcModel()
,
postprob()
,
predict.lcModel()
,
predictAssignments()
,
predictForCluster()
,
residuals.lcModel()
,
sigma.lcModel()
,
time.lcModel()