Bivariate Segmentation/Clustering Methods and Tools R package segclust2d version 0.3.3 CRAN Task View: Tracking (https://CRAN.R-project.org/view=Tracking) Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. Originally intended for ecological segmentation (home-range and behavioural modes) but easily applied on other series, the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' (Lavielle, 1999 <doi:10.1016/S0304-4149(99)00023-X> and 2005 <doi:10.1016/j.sigpro.2005.01.012>). This method rely on dynamic programming for efficient segmentation. The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. This is an extension of Picard et al (2007) <doi:10.1111/j.1541-0420.2006.00729.x> method (formerly available in 'cghseg' package) to the bivariate case. The method is fully described in Patin et al (2018) <doi:10.1101/444794>. Software Depends: R (>= 3.3.0) Imports: RColorBrewer (>= 1.1-2), dplyr (>= 1.0.0), plyr (>= 1.8.4), reshape2 (>= 1.4.1), ggplot2(>= 2.1.0), magrittr, Rcpp, zoo, grDevices, graphics, stats, utils, scales, rlang, methods, cli LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat, dygraphs (>= 1.1.1-1), xts (>= 0.9-7), leaflet (>= 1.0.1), sp (>= 1.2-3), adehabitatLT, depmixS4, moveHMM (>= 1.2), htmltools, move, devtools, spelling Remi Patin <remi.patin@normale.fr> Comprehensive R Archive Network (CRAN) Remi Patin [aut, cre], Marie-Pierre Etienne [aut], Emilie Lebarbier [aut], Simon Benhamou [aut] GPL-3 2024-04-24 application/tgz https://CRAN.R-project.org/package=segclust2d doi:10.32614/CRAN.package.segclust2d en-US