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: 2.0.2 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: 2025-02-01 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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=distantia to link to this page.
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