Obtain the proportional size per cluster, between 0 and 1.
clusterProportions(object, ...)
# S4 method for lcModel
clusterProportions(object, ...)The model.
For lcModel objects: Additional arguments passed to postprob().
A named numeric vector of length nClusters(object) with the proportional size of each cluster.
By default, the cluster proportions are determined from the cluster-averaged posterior probabilities of the fitted data (as computed by the postprob() function).
Classes extending lcModel can override this method to return, for example, the exact estimated mixture proportions based on the model coefficients.
setMethod("clusterProportions", "lcModelExt", function(object, ...) {
# return cluster proportion vector
})Other lcModel functions:
clusterNames(),
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(),
trajectoryAssignments()
data(latrendData)
method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time")
model <- latrend(method, latrendData, nClusters = 2)
clusterProportions(model)
#> A B
#> 0.6 0.4