Template vector, or unused if cost matrix given

Pointwise distance function. See e.g. <code><a href="/link/euclideanSquared?package=dtw&version=0.1-2" rd-options="" data-mini-rdoc="dtw::euclideanSquared">euclideanSquared</a></code>

distance.function

The step pattern. Char: "s" (symmetric), "a"
    (asymmetric), or an $s<times3>$ matrix containing the allowed
    steps with their cost -- to be documented better</times3>
  <item>window.type</item>{ Windowing function. Char: "none" (none, default),
    

step.pattern

Compute Dynamic Time Warp
  and find optimal alignment between two time series.

Implementation of Dynamic Time Warp (DTW) and its
	     generalizations. DTW finds the optimal mapping (local
	     time stretch) between a given query into a given template
	     time series. Implements symmetric, asymmetric, and custom
	     step patterns with weights. Supports windowing (none,
	     itakura, sakoe-chiba, custom).  DTW outputs minimum
	     cumulative distance, warping paths, etc.

dtw: Dynamic Time Warp

Description

Usage

Arguments