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


[Up] [Top]

Documentation for package ‘SNSeg’ version 1.0.3

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)