MAR                     A funtion to generate a multivariate
                        autoregressive process (MAR) in time series
MAR_MTS_Covariance      A Funtion to generate a multivariate
                        autoregressive process (MAR) model in time
                        series. It is used for testing change-points
                        based on the change in multivariate means or
                        multivariate covariance for multivariate time
                        series. It also works for the change in
                        correlations between two univariate time
                        series.
MAR_Variance            A funtion to generate a multivariate
                        autoregressive process (MAR) model in time
                        series for testing change points based on
                        variance and autocovariance
SNSeg                   SNSeg: An R Package for Time Series
                        Segmentation via Self-Normalization (SN)
SNSeg_HD                Self-normalization (SN) based change points
                        estimation for high dimensional time series for
                        changes in high-dimensional means (SNHD).
SNSeg_Multi             Self-normalization (SN) based change points
                        estimation for multivariate time series
SNSeg_Uni               Self-normalization (SN) based change point
                        estimates for univariate time series
SNSeg_estimate          Parameter estimates of each segment separated
                        by Self-Normalization (SN) based change-point
                        estimates
critical_values_HD      Critical Values of Self-Normalization (SN)
                        based test statistic for changes in
                        high-dimensional means (SNHD)
critical_values_multi   Critical Values of Self-Normalization (SN)
                        based test statistic for changes in multiple
                        parameters (SNCP)
critical_values_single
                        Critical Values of Self-Normalization (SN)
                        based test statistic for the change in a single
                        parameter (SNCP)
max_SNsweep             SN-based test statistic segmentation plot for
                        univariate, mulitivariate and high-dimensional
                        time series
plot.SNSeg_HD           Plotting the output for high-dimensional time
                        series with dimension greater than 10
plot.SNSeg_Multi        Plotting the output for multivariate time
                        series with dimension no greater than 10
plot.SNSeg_Uni          Plotting the output for univariate or bivariate
                        time series (testing the change in correlation
                        between bivariate time series)
print.SNSeg_HD          Print SN-based change-point estimates for
                        high-dimensional time series with dimension
                        greater than 10
print.SNSeg_Multi       Print SN-based change-point estimates for
                        multivariate time series with dimension no
                        greater than 10
print.SNSeg_Uni         Print SN-based change-point estimates for
                        univariate or bivariate time series (testing
                        the change in correlation between bivariate
                        time series)
summary.SNSeg_HD        Summary of SN-based change-point estimates for
                        high-dimensional time series with dimension
                        greater than 10
summary.SNSeg_Multi     Summary of SN-based change-point estimates for
                        multivariate time series with dimension no
                        greater than 10
summary.SNSeg_Uni       Summary of SN-based change-point estimates for
                        univariate or bivariate time series (testing
                        the change in correlation between bivariate
                        time series)
