Other packages > Find by keyword >

twdtw  

Time-Weighted Dynamic Time Warping
View on CRAN: Click here


Download and install twdtw package within the R console
Install from CRAN:
install.packages("twdtw")

Install from Github:
library("remotes")
install_github("cran/twdtw")

Install by package version:
library("remotes")
install_version("twdtw", "1.0-1")



Attach the package and use:
library("twdtw")
Maintained by
Victor Maus
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-13
Latest Update: 2023-08-08
Description:
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.
How to cite:
Victor Maus (2023). twdtw: Time-Weighted Dynamic Time Warping. R package version 1.0-1, https://cran.r-project.org/web/packages/twdtw. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0-0 (2023-07-13 16:10)
Other packages that cited twdtw R package
View twdtw citation profile
Other R packages that twdtw depends, imports, suggests or enhances
Complete documentation for twdtw
Functions, R codes and Examples using the twdtw R package
Some associated functions: date_to_numeric_cycle . max_cycle_length . plot_cost_matrix . print.twdtw . twdtw . 
Some associated R codes: RcppExports.R . convert_date_to_numeric.R . init.R . plot_cost_matrix.R . twdtw.R . zzz.R .  Full twdtw package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  
elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
Rfast2  
A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, ...
Download / Learn more Package Citations See dependency  
wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA