dist_afbdtw: Adaptive Feature Based Dynamic Time Warping algorithm

In DTWBI: Imputation of Time Series Based on Dynamic Time Warping

Adaptive Feature Based Dynamic Time Warping algorithm

Description

This function estimates a distance matrix which is used as an input in dtw() function (package dtw) to align two univariate signals following Adaptative Feature Based Dynamic Time Warping algorithm (AFBDTW).

Usage

dist_afbdtw(q, r, w1 = 0.5)

Arguments

q	query vector
r	reference vector
w1	weight of local feature VS global feature. By default, w1 = 0.5, and by definition, w2 = 1 - w1.

Value

A list containing the following elements:

query	The query vector.
response	The response vector.
query_local	Local features of the query.
response_local	Local features of the response vector.
query_global	Global features of the query.
response_global	Global features of the response vector.
dist_local	Distance matrix of the local features.
dist_global	Distance matrix of the global features.
distAFBDTW	AFBDTW distance matrix.

Examples

data(dataDTWBI)
X <- dataDTWBI[, 1] ; Y <- dataDTWBI[, 2]
AFBDTW_Dist <- dist_afbdtw(X, Y)

DTWBI documentation built on Sept. 9, 2026, 9:07 a.m.