R/generics.R
, R/model.R
predictAssignments.Rd
Predict the most likely cluster membership for each trajectory in the given data.
predictAssignments(object, newdata = NULL, ...)
# S4 method for class 'lcModel'
predictAssignments(object, newdata = NULL, strategy = which.max, ...)
The model.
A data.frame
of trajectory data for which to compute trajectory assignments.
Not used.
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.
A factor
of length nrow(newdata)
that indicates the assigned cluster per trajectory per observation.
The default implementation uses predictPostprob to determine the cluster membership.
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()
if (FALSE) { # \dontrun{
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))
}
} # }