dis_dtw_2 {mlmts} | R Documentation |
Constructs a pairwise distance matrix based on multivariate dynamic time warping
Description
dis_dtw_2
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_2(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 multivariate extension of the dynamic time warping distance which forces all dimensions to warp identically, in a single warping matrix.
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 : 10] # Selecting the first 10 MTS from the
# dataset AtrialFibrillation
distance_matrix <- dis_dtw_2(toy_dataset) # Computing the pairwise
# distance matrix based on the distance dis_dtw1 without normalization
distance_matrix_normalized <- dis_dtw_2(toy_dataset, normalization = TRUE)
# Computing the pairwise distance matrix based
# distance matrix based on the distance dis_dtw1 with normalization