View source: R/methodFunction.R
| lcMethodFunction | R Documentation |
Specify a custom method based on a function
lcMethodFunction(
response,
fun,
center = meanNA,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
name = "custom"
)
response |
The name of the response variable. |
fun |
The cluster |
center |
Optional |
time |
The name of the time variable. |
id |
The name of the trajectory identification variable. |
name |
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)
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