Longitudinal latent profile analysis
Latent profile analysis or finite Gaussian mixture modeling.
lcMethodMclustLLPA(
response,
time = getOption("latrend.time"),
id = getOption("latrend.id"),
nClusters = 2,
...
)response |
The name of the response variable. |
time |
The name of the time variable. |
id |
The name of the trajectory identifier variable. |
nClusters |
The number of clusters to estimate. |
... |
Arguments passed to mclust::Mclust. The following external arguments are ignored: data, G, verbose. |
Scrucca L, Fop M, Murphy TB, Raftery AE (2016). “mclust 5: clustering, classification and density estimation using Gaussian finite mixture models.” The R Journal, 8, 205–233. https://journal.r-project.org/archive/2016-1/scrucca-fop-murphy-etal.pdf.
Other lcMethod implementations:
lcMethod-class,
lcMethodAkmedoids,
lcMethodCrimCV,
lcMethodCustom,
lcMethodDtwclust,
lcMethodFeature,
lcMethodFunFEM,
lcMethodGCKM,
lcMethodKML,
lcMethodLMKM,
lcMethodLcmmGBTM,
lcMethodLcmmGMM,
lcMethodLongclust,
lcMethodMixAK_GLMM,
lcMethodMixtoolsGMM,
lcMethodMixtoolsNPRM,
lcMethodRandom,
lcMethodStratify
library(mclust)
data(latrendData)
method <- lcMethodMclustLLPA("Y", id = "Id", time = "Time", nClusters = 3)
model <- latrend(method, latrendData)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.