segclust2d

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.