dis_dtw_1 {mlmts} | R Documentation |
Constructs a pairwise distance matrix based on multivariate dynamic time warping
Description
dis_dtw_1
returns a pairwise distance matrix based on one of the multivariate
extensions of the well-known dynamic time warping distance (Shokoohi-Yekta et al. 2017).
Usage
dis_dtw_1(X, normalization = FALSE, ...)
Arguments
X |
A list of MTS (numerical matrices). |
normalization |
Logical. If |
... |
Additional parameters for the function. See |
Details
Given a collection of MTS, the function returns the pairwise distance matrix, where the distance between two MTS is defined as the sum of the standard dynamic time warping distances between each corresponding pair of dimensions (univariate time series)
Value
The computed pairwise distance matrix.
Author(s)
Ángel López-Oriona, José A. Vilar
References
Shokoohi-Yekta M, Hu B, Jin H, Wang J, Keogh E (2017). “Generalizing DTW to the multi-dimensional case requires an adaptive approach.” Data mining and knowledge discovery, 31(1), 1–31.
See Also
dis_dtw_2
, dis_mahalanobis_dtw
Examples
toy_dataset <- AtrialFibrillation$data[1 : 5] # Selecting the first 5 MTS from the
# dataset AtrialFibrillation
distance_matrix <- dis_dtw_1(toy_dataset) # Computing the pairwise
# distance matrix based on the distance dis_dtw_1 without normalization
distance_matrix_normalized <- dis_dtw_1(toy_dataset, normalization = TRUE)
# Computing the pairwise distance matrix based
# on the distance dis_dtw_1 with normalization