ARC                     Adversarially robust univariate mean change
                        point detection.
BD_U                    Backward detection with a robust bootstrap
                        change point test using U-statistics for
                        univariate mean change.
BS.cov                  Binary Segmentation for covariance change
                        points detection through Operator Norm.
BS.uni.nonpar           Standard binary segmentation for univariate
                        nonparametric change points detection.
BS.univar               Standard binary segmentation for univariate
                        mean change points detection.
CV.search.DP.LR.regression
                        Grid search based on Cross-Validation of all
                        tuning parameters (gamma, lambda and zeta) for
                        regression.
CV.search.DP.VAR1       Grid search based on cross-validation of
                        dynamic programming for VAR change points
                        detection via l_0 penalty.
CV.search.DP.poly       Grid search for dynamic programming to select
                        the tuning parameter through Cross-Validation.
CV.search.DP.regression
                        Grid search based on cross-validation of
                        dynamic programming for regression change
                        points detection via l_0 penalty.
CV.search.DP.univar     Grid search for dynamic programming to select
                        the tuning parameter through Cross-Validation.
DP.SEPP                 Dynamic programming for SEPP change points
                        detection through l_0 penalty.
DP.VAR1                 Dynamic programming for VAR1 change points
                        detection through l_0 penalty.
DP.poly                 Dynamic programming algorithm for univariate
                        polynomials change points detection.
DP.regression           Dynamic programming algorithm for regression
                        change points detection through l_0 penalty.
DP.univar               Dynamic programming for univariate mean change
                        points detection through l_0 penalty.
Hausdorff.dist          Bidirectional Hausdorff distance.
WBS.intervals           Generate random intervals for WBS.
WBS.multi.nonpar        Wild binary segmentation for multivariate
                        nonparametric change points detection.
WBS.network             Wild binary segmentation for network change
                        points detection.
WBS.nonpar.RDPG         Wild binary segmentation for dependent dynamic
                        random dot product graph models.
WBS.uni.nonpar          Wild binary segmentation for univariate
                        nonparametric change points detection.
WBS.uni.rob             Robust wild binary segmentation for univariate
                        mean change points detection.
WBS.univar              Wild binary segmentation for univariate mean
                        change points detection.
WBSIP.cov               Wild binary segmentation for covariance change
                        points detection through Independent
                        Projection.
aARC                    Automatic adversarially robust univariate mean
                        change point detection.
calibrate.online.network.missing
                        Calibrate step for online change point
                        detection for network data with missing values.
changepoints            changepoints-package: A Collections of
                        Change-Point Detection Methods
gen.cov.mat             Generate population covariance matrix with
                        dimension p.
gen.missing             Function to generate a matrix with values 0 or
                        1, where 0 indicating the entry is missing
gen.piece.poly          Generate univariate data from piecewise
                        polynomials of degree at most r.
gen.piece.poly.noiseless
                        Mean function of piecewise polynomials.
huber_mean              Element-wise adaptive Huber mean estimator.
lambda.network.missing
                        Function to compute the default thresholding
                        parameter for leading singular value in the
                        soft-impute algorithm.
local.refine.CV.VAR1    Local refinement for VAR1 change points
                        detection.
local.refine.VAR1       Local refinement for VAR1 change points
                        detection.
local.refine.network    Local refinement for network change points
                        detection.
local.refine.poly       Local refinement for univariate polynomials
                        change point detection.
local.refine.regression
                        Local refinement for regression change points
                        detection.
local.refine.univar     Local refinement of an initial estimator for
                        univariate mean change points detection.
lowertri2mat            Transform a vector containing lower diagonal
                        entries into a symmetric matrix of dimension p.
online.network          Online change point detection for network data.
online.network.missing
                        Online change point detection for network data
                        with missing values.
online.univar           Online change point detection with controlled
                        false alarm rate or average run length.
online.univar.multi     Online change point detection with potentially
                        multiple change points.
simu.RDPG               Simulate a dot product graph (without change
                        point).
simu.SBM                Simulate a Stochastic Block Model (without
                        change point).
simu.SEPP               Simulate a (stable) SEPP model (without change
                        point).
simu.VAR1               Simulate from a VAR1 model (without change
                        point).
simu.change.regression
                        Simulate a sparse regression model with change
                        points in coefficients.
softImpute.network.missing
                        Estimate graphon matrix by soft-impute for
                        independent adjacency matrices with missing
                        values.
thresholdBS             Thresholding a BS object with threshold value
                        tau.
tuneBSmultinonpar       A function to compute change points based on
                        the multivariate nonparametic method with
                        tuning parameter selected by FDR control.
tuneBSnonparRDPG        Change points detection for dependent dynamic
                        random dot product graph models.
tuneBSuninonpar         Wild binary segmentation for univariate
                        nonparametric change points detection with
                        tuning parameter selection.
tuneBSunivar            Univariate mean change points detection based
                        on standard or wild binary segmentation with
                        tuning parameter selected by sSIC.
