lcMethodRandom | R Documentation |
Creates a model with random cluster assignments according to the random cluster proportions drawn from a Dirichlet distribution.
lcMethodRandom(
response,
alpha = 10,
center = meanNA,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
nClusters = 2,
name = "random",
...
)
response |
The name of the response variable. |
alpha |
The Dirichlet parameters. Either |
center |
Optional |
time |
The name of the time variable. |
id |
The name of the trajectory identification variable. |
nClusters |
The number of clusters. |
name |
The name of the method. |
... |
Additional arguments, such as the seed. |
frigyik2010introductionlatrend
Other lcMethod implementations:
getArgumentDefaults()
,
getArgumentExclusions()
,
lcMethod-class
,
lcMethodAkmedoids
,
lcMethodCrimCV
,
lcMethodDtwclust
,
lcMethodFeature
,
lcMethodFunFEM
,
lcMethodFunction
,
lcMethodGCKM
,
lcMethodKML
,
lcMethodLMKM
,
lcMethodLcmmGBTM
,
lcMethodLcmmGMM
,
lcMethodMclustLLPA
,
lcMethodMixAK_GLMM
,
lcMethodMixtoolsGMM
,
lcMethodMixtoolsNPRM
,
lcMethodStratify
data(latrendData)
method <- lcMethodRandom(response = "Y", id = "Id", time = "Time")
model <- latrend(method, latrendData)
# uniform clusters
method <- lcMethodRandom(
alpha = 1e3,
nClusters = 3,
response = "Y",
id = "Id",
time = "Time"
)
# single large cluster
method <- lcMethodRandom(
alpha = c(100, 1, 1, 1),
nClusters = 4,
response = "Y",
id = "Id",
time = "Time"
)
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