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Many methods and models (e.g., lcModelPartition, lcMethodStratify) depend on a non-parametric estimate of the cluster trajectories based on the original data. Having a standard exported method clusterTrajectories() with signature data.frame for computing such cluster trajectories would make it more transparent to users how these centers are generated, and which additional arguments are available (which could be provided through the method specification).
Moreover, it enables users to use the center computation in their own models.
Define clusterTrajectories(data.frame, assignments, center = meanNA, at = numeric())
Move functionality of computeCenterClusterTrajectories() to clusterTrajectories(data.frame)
Update methods and models using any type of center specification
Extend clusterTrajectories(data.frame) to interpolate between measurements.
The text was updated successfully, but these errors were encountered:
niekdt
changed the title
clusterTrajectories() for data.frame
Standard (interpolated) non-parametric cluster trajectory estimation through lcModelPartition and lcModelWeightedPartition
Oct 20, 2021
On second thought, this functionality is better moved to lcModelPartition and lcModelWeightedPartition. Otherwise, the clusterTrajectories(data.frame) function would need two handle two cases:
Hard partition, with a center function that accepts a data vector
Fuzzy partition, with a center function accepting the full data vector along with a weight argument
Move hard cluster trajectory computation code inside clusterTrajectories(lcModelPartition)
Extend clusterTrajectories(lcModelPartition) to interpolate between measurements.
Many methods and models (e.g.,
lcModelPartition
,lcMethodStratify
) depend on a non-parametric estimate of the cluster trajectories based on the original data. Having a standard exported methodclusterTrajectories()
with signaturedata.frame
for computing such cluster trajectories would make it more transparent to users how these centers are generated, and which additional arguments are available (which could be provided through the method specification).Moreover, it enables users to use the center computation in their own models.
clusterTrajectories(data.frame, assignments, center = meanNA, at = numeric())
computeCenterClusterTrajectories()
toclusterTrajectories(data.frame)
center
specificationclusterTrajectories(data.frame)
to interpolate between measurements.The text was updated successfully, but these errors were encountered: