lcMethodLMKM {latrend} | R Documentation |
Two-step clustering through linear regression modeling and k-means
Description
Two-step clustering through linear regression modeling and k-means
Usage
lcMethodLMKM(
formula,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
nClusters = 2,
center = meanNA,
standardize = scale,
...
)
Arguments
formula |
A |
time |
The name of the time variable. |
id |
The name of the trajectory identification variable. |
nClusters |
The number of clusters to estimate. |
center |
A |
standardize |
A |
... |
Arguments passed to stats::lm. The following external arguments are ignored: x, data, control, centers, trace. |
See Also
Other lcMethod implementations:
getArgumentDefaults()
,
getArgumentExclusions()
,
lcMethod-class
,
lcMethodAkmedoids
,
lcMethodCrimCV
,
lcMethodDtwclust
,
lcMethodFeature
,
lcMethodFunFEM
,
lcMethodFunction
,
lcMethodGCKM
,
lcMethodKML
,
lcMethodLcmmGBTM
,
lcMethodLcmmGMM
,
lcMethodMclustLLPA
,
lcMethodMixAK_GLMM
,
lcMethodMixtoolsGMM
,
lcMethodMixtoolsNPRM
,
lcMethodRandom
,
lcMethodStratify
Examples
data(latrendData)
method <- lcMethodLMKM(Y ~ Time, id = "Id", time = "Time", nClusters = 3)
model <- latrend(method, latrendData)