dtwclust-class: Class definition for `dtwclust`

Description

Formal S4 class.

Arguments

Slots

call: The function call.
control: An object of class dtwclustControl.
family: An object of class dtwclustFamily.
distmat: If computed, the cross-distance matrix.
k: Integer indicating the number of desired clusters.
cluster: Integer vector indicating which cluster a series belongs to (crisp partition).
fcluster: Numeric 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.
iter: The number of iterations used.
converged: A logical indicating whether the function converged.
clusinfo: A data frame with two columns: size indicates the number of series each cluster has, and av_dist indicates the average distance between series of each cluster (crisp partition).
centers: A list with the centroid time series.
cldist: A column vector with the distance between each series in the data and its corresponding centroid (crisp partition).
type: A string indicating one of the supported clustering types of dtwclust.
method: A string indicating which hierarchical method was used.
distance: A string indicating the distance used.
centroid: A string indicating the centroid used.
preproc: A string indicating the preprocessing used.
datalist: The provided data in the form of a list, where each element is a time series.
proctime: Time during function execution, as measured with proc.time.

Details

This class contains hclust as superclass and supports all its methods. Plot is a special case (see dtwclust-methods).

Please note that not all slots will contain valid information for all clustering types. In some cases, for example for fuzzy and hierarchical clustering, some results are computed assuming a hard partition is created based on the fuzzy memberships or dendrogram tree, and the provided value of k.