| TSClusters-class | R Documentation |
TSClusters and derived classesFormal S4 classes for time-series clusters. See class hierarchy and slot organization at the bottom.
The base class is TSClusters. The 3 classes that inherit from it are: PartitionalTSClusters,
HierarchicalTSClusters and FuzzyTSClusters.
HierarchicalTSClusters also contain stats::hclust() as parent class.
Package clue is supported, but generics from flexclust are not. See also TSClusters-methods.
callThe function call.
familyAn object of class tsclustFamily.
controlAn appropriate control object for tsclust(). See tsclust-controls.
datalistThe provided data in the form of a list, where each element is a time series.
typeA string indicating one of the supported clustering types of tsclust().
distanceA string indicating the distance used.
centroidA string indicating the centroid used.
preprocA string indicating the preprocessing used.
kInteger indicating the number of desired clusters.
clusterInteger vector indicating which cluster a series belongs to (crisp partition). For
fuzzy clustering, this is based on distance, not on fcluster. For hierarchical, this is
obtained by calling stats::cutree() with the given value of k.
centroidsA list with the centroid time series.
distmatIf computed, the cross-distance matrix.
proctimeTime during function execution, as measured with base::proc.time().
dotsThe contents of the original call's ellipsis (...).
argsThe contents of the original call's args parameter. See tsclust_args().
seedThe random seed that was used.
iterThe number of iterations used.
convergedA logical indicating whether the function converged.
clusinfoA data frame with two columns: size indicates the number of series each cluster
has, and av_dist indicates, for each cluster, the average distance between series and their
respective centroids (crisp partition).
cldistA column vector with the distance between each series in the data and its corresponding centroid (crisp partition).
methodA string indicating which hierarchical method was used.
fclusterNumeric matrix that contains membership of fuzzy clusters. It has one row for each series and one column for each cluster. The rows must sum to 1. Only relevant for fuzzy clustering.
The base class contains the following slots:
call
family
control
datalist
type
distance
centroid
preproc
k
cluster
centroids
distmat
proctime
dots
args
seed
This class adds the following slots to the base class:
iter
converged
clusinfo
cldist
This class adds the following slots to the base class:
method
clusinfo
cldist
This class adds the following slots to the base class:
iter
converged
fcluster
TSClusters-methods
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