Create a lcModel with pre-defined partitioning
Represents an arbitrary partitioning of a set of trajectories. As such, this model has no predictive capabilities. The cluster trajectories are represented by the specified center function (mean by default).
lcModelPartition( data, response, trajectoryAssignments, nClusters = NA, center = meanNA, clusterNames = NULL, time = getOption("latrend.time"), id = getOption("latrend.id"), name = "part", envir = parent.frame() )
data |
A |
response |
The name of the response variable. |
trajectoryAssignments |
A |
nClusters |
The number of clusters. Optional for |
center |
The |
clusterNames |
The names of the clusters, or a function with input |
time |
The name of the time variable. |
id |
The name of the trajectory identification variable. |
name |
The name of the method. |
envir |
The |
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