| 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) |
| 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 |
| max_SNsweep | SN-based test statistic segmentation plot for univariate, mulitivariate and high-dimensional time series |
| 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 |