twdtw

Implements Time-Weighted Dynamic Time Warping (TWDTW), a measure for quantifying time series similarity. The TWDTW algorithm, described in Maus et al. (2016) doi:10.1109/JSTARS.2016.2517118 and Maus et al. (2019) doi:10.18637/jss.v088.i05, is applicable to multi-dimensional time series of various resolutions. It is particularly suitable for comparing time series with seasonality for environmental and ecological data analysis, covering domains such as remote sensing imagery, climate data, hydrology, and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, efficient 'Fortran' routines for TWDTW calculations, flexible time weighting definitions, as well as utilities for time series preprocessing and visualization.

Last 30 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.