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segclust2d  

Bivariate Segmentation/Clustering Methods and Tools
View on CRAN: Click here


Download and install segclust2d package within the R console
Install from CRAN:
install.packages("segclust2d")

Install from Github:
library("remotes")
install_github("cran/segclust2d")

Install by package version:
library("remotes")
install_version("segclust2d", "0.3.3")



Attach the package and use:
library("segclust2d")
Maintained by
Remi Patin
[Scholar Profile | Author Map]
First Published: 2018-02-23
Latest Update: 2023-08-21
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 and 2005 ). 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) method (formerly available in 'cghseg' package) to the bivariate case. The method is fully described in Patin et al (2018) .
How to cite:
Remi Patin (2018). segclust2d: Bivariate Segmentation/Clustering Methods and Tools. R package version 0.3.3, https://cran.r-project.org/web/packages/segclust2d. Accessed 19 Apr. 2025.
Previous versions and publish date:
0.1.0 (2018-02-23 20:25), 0.2.0 (2019-02-27 18:00), 0.3.0 (2021-10-11 10:10), 0.3.1 (2023-08-21 10:50)
Other packages that cited segclust2d R package
View segclust2d citation profile
Other R packages that segclust2d depends, imports, suggests or enhances
Complete documentation for segclust2d
Functions, R codes and Examples using the segclust2d R package
Some associated functions: DynProg . DynProg_algo_cpp . EM.algo_simultanee . EM.algo_simultanee_Cpp . EM.init_simultanee . Estep_simultanee . Gmean_simultanee . Gmixt_algo_cpp . Gmixt_simultanee . Gmixt_simultanee_fullcpp . Mstep_simultanee . Mstep_simultanee_cpp . add_covariates . angular_speed . apply_rowSums . apply_subsampling . argcheck_Kmax . argcheck_diag.var . argcheck_lmin . argcheck_ncluster . argcheck_order.var . argcheck_ordering . argcheck_scale.variable . argcheck_seg.var . argcheck_segclust . argcheck_segmentation . argcheck_type_coord . arma_repmat . augment . bisig_plot . calc_BIC . calc_dist . calc_speed . calc_stat_states . check_repetition . choose_kmax . chooseseg_lavielle . colsums_sapply . cumsum_cpp . find_mu_sd . hybrid_simultanee . initialisePhi . likelihood . logdens_simultanee . map_segm . matrixRupt . neighborsbis . plot_segm . plot_states . prep_segm . prep_segm_HMM . prep_segm_shiftfit . prepare_HMM . prepare_shiftfit . relabel_states . repmat . ruptAsMat . segclust . segclust2d . segclust_internal . segmap_list . segmentation-class . segmentation . simulmode . simulshift . spatial_angle . stat_segm . stat_segm_HMM . stat_segm_shiftfit . subsample_rename . test_data . wrap_dynprog_cpp . 
Some associated R codes: Ex_data.R . RcppExports.R . SegTraj_EM_cpp.R . augment_generic.R . choose_Kmax.R . function_checks.R . function_map_plot.R . function_prepare.R . function_series_plot.R . function_states_plot.R . likelihood_generic.R . prepare_HMM.R . prepare_covariates.R . prepare_shiftfit.R . segTraj_DynProg.R . segTraj_EM.algo_simultanee.R . segTraj_EM.init_simultanee.R . segTraj_Estep_simultanee.R . segTraj_Gmean_simultanee.R . segTraj_Gmixt_simultanee.R . segTraj_Mstep_simultanee.R . segTraj_hybrid_simultanee.R . segTraj_initialisePhi.R . segTraj_logdens_simultanee.R . segTraj_neighborsbis.R . segTraj_plot_simultanee.R . segTraj_repmat.R . segTraj_ruptAsMat.R . segclust.R . segclust2d.R . segmentation.R . segmentation_class.R . test_functions.R . tools.R .  Full segclust2d package functions and examples
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