# Bivariate Segmentation/Clustering Methods and Tools

## Documentation for package ‘segclust2d’ version 0.3.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

segclust2d-package | segclust2d: tools for segmentation of animal GPS movement data
add_covariates | Covariate Calculations
add_covariates.data.frame | Covariate Calculations
add_covariates.ltraj | Covariate Calculations
add_covariates.Move | Covariate Calculations
angular_speed | Calculate angular speed along a path
apply_rowSums | apply_rowSums
apply_subsampling | Internal function for subsampling
argcheck_diag.var | Check for argument 'diag.var'
argcheck_Kmax | Check for argument 'Kmax'
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
augment.segmentation | segmentation class description
BIC.segmentation | segmentation class description
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
chooseseg_lavielle | Internal Function for choosing optimal number of segment
choose_kmax | Finding best segmentation with a different threshold S
colsums_sapply | colsums_sapply
cumsum_cpp | cumsum_cpp
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
find_mu_sd | Find mean and standard deviation of segments
get_likelihood | segmentation class description
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
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
likelihood.segmentation | segmentation class description
logdens_simultanee | logdens_simultanee_cpp
logdens_simultanee_cpp | logdens_simultanee_cpp
logLik.segmentation | segmentation class description
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
Mstep_simultanee | Mstep_simultanee computes the MLE within the EM framework
Mstep_simultanee_cpp | Mstep_simultanee computes the MLE within the EM framework
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.segmentation | segmentation class description
plot_BIC | segmentation class description
plot_likelihood | segmentation class description
plot_segm | Plot segmentation on time-serie
plot_states | Plot states statistics
prepare_HMM | Prepare HMM output for proper comparison plots
prepare_shiftfit | Prepare shiftfit output for proper comparison plots
prep_segm | Find segment and states for a Picard model
prep_segm_HMM | Internal function for HMM
prep_segm_shiftfit | Internal function for HMM
print.segmentation | segmentation class description
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
segclust.data.frame | Segmentation/Clustering of movement data - Generic function
segclust.ltraj | Segmentation/Clustering of movement data - Generic function
segclust.Move | Segmentation/Clustering of movement data - Generic function
segclust2d | segclust2d: tools for segmentation of animal GPS movement data
segclust_internal | Internal segmentation/clustering function
segmap | segmentation class description
segmap_list | 'segmap_list' create maps with a list of object of 'segmentation' class
segment | segmentation class description
segmentation | Segmentation of movement data - Generic function
segmentation-class | segmentation class description
segmentation.data.frame | Segmentation of movement data - Generic function
segmentation.ltraj | Segmentation of movement data - Generic function
segmentation.Move | Segmentation of movement data - Generic function
segmentation_internal | Segmentation of movement data - Generic function
simulmode | Simulations of behavioural mode
simulshift | Simulations of home-range shift
spatial_angle | Calculate spatial angle along a path
stateplot | segmentation class description
states | segmentation class description
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