R: Self-Normalization(SN) Based Change-Point Estimation for Time Series

# Self-Normalization(SN) Based Change-Point Estimation for Time Series

## Documentation for package ‘SNSeg’ version 1.0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

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
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)
SNSeg | SNSeg: An R Package for Time Series Segmentation via Self-Normalization (SN)
SNSeg_estimate | Parameter estimates of each segment separated by Self-Normalization (SN) based change-point estimates
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
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)