Specify a custom method based on a function
The name of the response variable.
The cluster function
with signature (method, data)
that returns a lcModel
object.
Optional function
for computing the longitudinal cluster centers, with signature (x)
.
The name of the time variable.
The name of the trajectory identification variable.
The name of the method.
Other lcMethod implementations:
getArgumentDefaults()
,
getArgumentExclusions()
,
lcMethod-class
,
lcMethodAkmedoids
,
lcMethodCrimCV
,
lcMethodDtwclust
,
lcMethodFeature
,
lcMethodFunFEM
,
lcMethodGCKM
,
lcMethodKML
,
lcMethodLMKM
,
lcMethodLcmmGBTM
,
lcMethodLcmmGMM
,
lcMethodMclustLLPA
,
lcMethodMixAK_GLMM
,
lcMethodMixtoolsGMM
,
lcMethodMixtoolsNPRM
,
lcMethodRandom
,
lcMethodStratify
data(latrendData)
# Stratification based on the mean response level
clusfun <- function(data, response, id, time, ...) {
clusters <- data.table::as.data.table(data)[, mean(Y) > 0, by = Id]$V1
lcModelPartition(
data = data,
trajectoryAssignments = factor(
clusters,
levels = c(FALSE, TRUE),
labels = c("Low", "High")
),
response = response,
time = time,
id = id
)
}
method <- lcMethodFunction(response = "Y", fun = clusfun, id = "Id", time = "Time")
model <- latrend(method, data = latrendData)