dis_www {mlmts}

Constructs a pairwise distance matrix based on feature extraction

Description

dis_www returns a pairwise distance matrix based on the feature extraction procedure proposed by Wang et al. (2007).

Usage

dis_www(X, h = 20, features = FALSE)

Arguments

X

A list of MTS (numerical matrices).

h

Maximum lag for the computation of the Box-Pierce statistic.

features

Logical. If features = FALSE (default), a distance matrix is returned. Otherwise, the function returns a dataset of feature vectors.

Details

Given a collection of MTS, the function returns the pairwise distance matrix, where the distance between two MTS is defined as the Euclidean distance between the corresponding feature vectors

Value

If features = FALSE (default), returns a distance matrix based on the distance d_{WWW}. Otherwise, the function returns a dataset of feature vectors, i.e., each row in the dataset contains the features employed to compute the distance d_{WWW}.

Author(s)

Ángel López-Oriona, José A. Vilar

References

Wang X, Wirth A, Wang L (2007). “Structure-based statistical features and multivariate time series clustering.” In Seventh IEEE international conference on data mining (ICDM 2007), 351–360. IEEE.

Examples

toy_dataset <- AtrialFibrillation$data[1 : 10] # Selecting the first 10 MTS from the
# dataset AtrialFibrillation
distance_matrix <- dis_www(toy_dataset) # Computing the pairwise
# distance matrix based on the distance dis_www
feature_dataset <- dis_www(toy_dataset, features = TRUE) # Computing
# the corresponding dataset of features