distantia: Advanced Toolset for Efficient Time Series Dissimilarity
Analysis
Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.
| Version: |
2.0.0 |
| Depends: |
R (≥ 4.1), doFuture |
| Imports: |
Rcpp, zoo, foreach, future.apply, lubridate, progressr |
| LinkingTo: |
Rcpp |
| Suggests: |
roxyglobals, spelling, sf, lwgeom, testthat (≥ 3.0.0) |
| Published: |
2025-01-08 |
| DOI: |
10.32614/CRAN.package.distantia |
| Author: |
Blas M. Benito 
[aut, cre, cph] |
| Maintainer: |
Blas M. Benito <blasbenito at gmail.com> |
| BugReports: |
https://github.com/BlasBenito/distantia/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://blasbenito.github.io/distantia/ |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Citation: |
distantia citation info |
| Materials: |
README NEWS |
| CRAN checks: |
distantia results |
Documentation:
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