Package: segclust2d
Type: Package
Title: Bivariate Segmentation/Clustering Methods and Tools
Version: 0.2.0
Authors@R: c(person("Remi", "Patin", role = c("aut", "cre"), email = "remi.patin@normale.fr"),
             person("Marie-Pierre", "Etienne", role = "aut"), 
             person("Emilie", "Lebarbier", role = "aut"), 
             person("Simon", "Benhamou", role = "aut"))
Description: 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>.
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Depends: R (>= 3.3.0)
Imports: RColorBrewer (>= 1.1-2), dplyr (>= 0.5.0), plyr (>= 1.8.4),
        reshape2 (>= 1.4.1), ggplot2(>= 2.1.0), magrittr, Rcpp, zoo,
        grDevices, graphics, stats, utils, scales
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
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-02-27 13:54:34 UTC; patin
Author: Remi Patin [aut, cre],
  Marie-Pierre Etienne [aut],
  Emilie Lebarbier [aut],
  Simon Benhamou [aut]
Maintainer: Remi Patin <remi.patin@normale.fr>
Repository: CRAN
Date/Publication: 2019-02-27 17:00:08 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 08:24:33 UTC; windows
Archs: i386, x64
