segclust2d: Bivariate Segmentation/Clustering Methods and Tools (original) (raw)

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>.

Version:

0.3.3

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