Feature-based clustering.
lcMethodFeature(
response,
representationStep,
clusterStep,
standardize = scale,
center = meanNA,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
...
)The name of the response variable.
A function with signature function(method, data) that computes the representation per strata, returned as a matrix.
Alternatively, representationStep is a pre-computed representation matrix.
A function with signature function(repdata) that outputs a lcModel.
A function to standardize the output matrix of the representation step. By default, the output is shifted and rescaled to ensure zero mean and unit variance.
Optional function for computing the longitudinal cluster centers, with signature (x).
The name of the time variable.
The name of the trajectory identification variable.
Additional arguments.
Other lcMethod implementations:
lcMethod-class,
lcMethodAkmedoids,
lcMethodCrimCV,
lcMethodCustom,
lcMethodDtwclust,
lcMethodFunFEM,
lcMethodGCKM,
lcMethodKML,
lcMethodLMKM,
lcMethodLcmmGBTM,
lcMethodLcmmGMM,
lcMethodLongclust,
lcMethodMclustLLPA,
lcMethodMixAK_GLMM,
lcMethodMixtoolsGMM,
lcMethodMixtoolsNPRM,
lcMethodRandom,
lcMethodStratify