Nothing
## ----setup, include = FALSE---------------------------------------------------
set.seed(1)
knitr::opts_chunk$set(
cache = TRUE,
collapse = TRUE,
fig.width = 7,
fig.align = "center",
fig.topcaption = TRUE,
comment = "#>",
eval = all(vapply(c('ggplot2', 'kml', 'lme4', 'mclustcomp'), requireNamespace, FUN.VALUE = TRUE, quietly = TRUE)) # needed to prevent errors for _R_CHECK_DEPENDS_ONLY_=true despite VignetteDepends declaration
)
## ---- results='hide',message=FALSE,warning=FALSE------------------------------
library(latrend)
library(ggplot2)
## -----------------------------------------------------------------------------
data(latrendData)
head(latrendData)
## -----------------------------------------------------------------------------
options(latrend.id = "Id", latrend.time = "Time")
## ---- fig.asp = .6, fig.cap='Visualizing the trajectories of the `latrend` dataset.'----
plotTrajectories(latrendData, response = "Y")
## -----------------------------------------------------------------------------
kmlMethod <- lcMethodKML(response = "Y", nClusters = 2, nbRedrawing = 1)
kmlMethod
## -----------------------------------------------------------------------------
kmlModel <- latrend(kmlMethod, data = latrendData)
## -----------------------------------------------------------------------------
kmlModel
## -----------------------------------------------------------------------------
kmlMethods <- lcMethods(kmlMethod, nClusters = 1:7)
as.data.frame(kmlMethods)
## -----------------------------------------------------------------------------
kmlModels <- latrendBatch(kmlMethods, data = latrendData, verbose = FALSE)
kmlModels
## ----warning=FALSE, fig.cap = 'Elbow plots of three relevant cluster metrics across the fitted models.'----
plotMetric(kmlModels, c("logLik", "BIC", "WMAE"))
## -----------------------------------------------------------------------------
kmlModel4 <- subset(kmlModels, nClusters == 4, drop = TRUE)
kmlModel4
## ---- fig.cap = 'Cluster trajectories for KML model with 4 clusters.'---------
plotClusterTrajectories(kmlModel4)
## ---- fig.asp = .8, fig.cap = 'Cluster trajectories for KML model with 4 clusters, along with the assigned trajectories.'----
plot(kmlModel4)
## -----------------------------------------------------------------------------
getInternalMetricNames()
## -----------------------------------------------------------------------------
metric(kmlModel, c("APPA.mean", "WRSS", "WMAE"))
## ---- fig.width = 5, fig.cap = 'QQ-plot of the selected KML model.'-----------
qqPlot(kmlModel4)
## ---- fig.asp = .8, fig.cap = 'Cluster-specific detrended QQ-plot for the selected KML model.'----
qqPlot(kmlModel4, byCluster = TRUE, detrend = TRUE)
## -----------------------------------------------------------------------------
lmkmMethod <- lcMethodLMKM(formula = Y ~ Time)
lmkmMethod
## ---- echo=TRUE, results='hide'-----------------------------------------------
lmkmMethods <- lcMethods(lmkmMethod, nClusters = 1:5)
lmkmModels <- latrendBatch(lmkmMethods, data = latrendData, verbose = FALSE)
## ----warning=FALSE, fig.cap = 'Three cluster metrics for each of the GBTMs.'----
plotMetric(lmkmModels, c("logLik", "BIC", "WMAE"))
## -----------------------------------------------------------------------------
bestLmkmModel <- subset(lmkmModels, nClusters == 3, drop=TRUE)
plot(bestLmkmModel)
## ---- fig.width = 5, fig.cap = 'Non-parametric estimates of the cluster trajectories based on the reference assignments.'----
plotClusterTrajectories(latrendData, response = "Y", cluster = "Class")
## -----------------------------------------------------------------------------
refTrajAssigns <- aggregate(Class ~ Id, data = latrendData, FUN = data.table::first)
refModel <- lcModelPartition(data = latrendData, response = "Y", trajectoryAssignments = refTrajAssigns$Class)
refModel
## ---- fig.cap = 'Cluster trajectories of the reference model.'----------------
plot(refModel)
## -----------------------------------------------------------------------------
getExternalMetricNames()
## -----------------------------------------------------------------------------
externalMetric(bestLmkmModel, refModel, "adjustedRand")
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