DynProg                 DynProg computes the change points given a cost
                        matrix matD and a maximum number of segments
                        Kmax
DynProg_algo_cpp        DynProg_algo_cpp
EM.algo_simultanee      EM.algo_simultanee calculates the MLE of phi
                        for given change-point instants
EM.algo_simultanee_Cpp
                        EM.algo_simultanee calculates the MLE of phi
                        for given change-point instants and for a fixed
                        number of clusters
EM.init_simultanee      EM.init_simultanee proposes an initial value
                        for the EM algorithm based on a hierarchical
                        clustering algorithm (ascending)
Estep_simultanee        Estep_simultanee computes posterior
                        probabilities and incomplete-data
                        log-likelihood for mixture models
Gmean_simultanee        Gmean_simultanee calculates the cost matrix for
                        a segmentation model with changes in the mean
                        and variance for all signals
Gmixt_algo_cpp          Gmixt_algo_cpp
Gmixt_simultanee        Gmixt_simultanee calculates the cost matrix for
                        a segmentation/clustering model
Gmixt_simultanee_fullcpp
                        Gmixt_simultanee_fullcpp
Mstep_simultanee        Mstep_simultanee computes the MLE within the EM
                        framework
Mstep_simultanee_cpp    Mstep_simultanee computes the MLE within the EM
                        framework
add_covariates          Covariate Calculations
angular_speed           Calculate angular speed along a path
apply_rowSums           apply_rowSums
apply_subsampling       Internal function for subsampling
argcheck_Kmax           Check for argument 'Kmax'
argcheck_diag.var       Check for argument 'diag.var'
argcheck_lmin           Check for argument 'lmin'
argcheck_ncluster       Check for argument 'ncluster'
argcheck_order.var      Check for argument 'order.var'
argcheck_ordering       Check for argument 'order'
argcheck_scale.variable
                        Check for argument 'scale.variable'
argcheck_seg.var        Check for argument 'seg.var'
argcheck_segclust       Check for argument 'ncluster' and 'nseg'
argcheck_segmentation   Check for argument 'nseg'
argcheck_type_coord     Check for deprecated 'type' and 'coord.names'
                        argument
arma_repmat             arma_repmat
augment                 Generic function for augment
bisig_plot              bisig_plot draws the plots of the bivariate
                        signal on the same plot (scale free)
calc_BIC                Calculate BIC
calc_dist               Calculate distance between locations
calc_speed              Calculate speed along a path
calc_stat_states        Calculate state statistics
check_repetition        Check for repetition in the series
choose_kmax             Finding best segmentation with a different
                        threshold S
chooseseg_lavielle      Internal Function for choosing optimal number
                        of segment
colsums_sapply          colsums_sapply
cumsum_cpp              cumsum_cpp
find_mu_sd              Find mean and standard deviation of segments
hybrid_simultanee       'hybrid_simultanee' performs a simultaneous seg
                        - clustering for bivariate signals.
initialisePhi           initialisePhi is the constructor for a set of
                        parameters for a segclust model
likelihood              Generic function for likelihood
logdens_simultanee_cpp
                        logdens_simultanee_cpp
map_segm                'plot_segm' plot segmented movement data on a
                        map.
matrixRupt              matrixRupt transforms a vector of change point
                        into a data.frame with start and end of every
                        segment
neighborsbis            neighbors tests whether neighbors of point k,P
                        can be used to re-initialize the EM algorithm
                        and to improve the log-likelihood.
plot_segm               Plot segmentation on time-serie
plot_states             Plot states statistics
prep_segm               Find segment and states for a Picard model
prep_segm_HMM           Internal function for HMM
prep_segm_shiftfit      Internal function for HMM
prepare_HMM             Prepare HMM output for proper comparison plots
prepare_shiftfit        Prepare shiftfit output for proper comparison
                        plots
relabel_states          Relabel states of a segmentation/clustering
                        output
repmat                  repmat repeats a matrix
ruptAsMat               ruptAsMat is an internal function to transform
                        a vector giving the change point to matrix 2
                        columns matrix in which each line gives the
                        beginning and the end of a segment
segclust                Segmentation/Clustering of movement data -
                        Generic function
segclust2d              segclust2d: tools for segmentation of animal
                        GPS movement data
segclust_internal       Internal segmentation/clustering function
segmap_list             'segmap_list' create maps with a list of object
                        of 'segmentation' class
segmentation            Segmentation of movement data - Generic
                        function
segmentation-class      segmentation class description
simulmode               Simulations of behavioural mode
simulshift              Simulations of home-range shift
spatial_angle           Calculate spatial angle along a path
stat_segm               Calculate statistics on a given segmentation
stat_segm_HMM           Get segment statistic for HMM model
stat_segm_shiftfit      Get segment statistic for shiftfit model
subsample_rename        Internal function for subsampling
test_data               Test function generating fake data
wrap_dynprog_cpp        DynProg Rcpp DynProg computes the change points
                        given a cost matrix matD and a maximum number
                        of segments Kmax
