L2 Inference for Change Points in High-Dimensional Time Series

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Documentation for package ‘L2hdchange’ version 1.0

Help Pages

check_nbd Check the validity of the neighbourhood specification
covid_data U.S. COVID-19 Data
covid_nbd_info U.S. COVID-19 Data Neighbourhood Information
est_hdchange Construct an S3 class 'no_nbd' or 'nbd' for change-point estimation
genZ Generate a random Gaussian vector
get_breaks Obtain the time-stamps and spatial locations with breaks
get_breaks.nbd Obtain the time-stamps and spatial locations with breaks
get_breaks.no_nbd Obtain the time-stamps and spatial locations without break
get_cov_x_MAinf The covariance matrix for generating random Gaussian vector
get_critical Obtain critical values and threshold
get_critical.nbd Obtain critical values and threshold
get_critical.no_nbd Obtain critical values and threshold
get_GS_MAinf Obtain the simulated standardised gap vector
get_GS_MAinf.nbd Obtain the simulated standardised gap vector
get_GS_MAinf.no_nbd Obtain the simulated standardised gap vector
get_lr_var Compute the long-run variance of the gap vector
get_teststats Obtain the test statistics
get_teststats.nbd Obtain the test statistics
get_teststats.no_nbd Obtain the test statistics
get_V_l2_MAinf Obtain the standardised gap vector
get_V_l2_MAinf.nbd Obtain the standardised gap vector
get_V_l2_MAinf.no_nbd Obtain the standardised gap vector
hdchange Estimate the time-stamps and spatial locations with breaks
plot_result Plot the time series and change-points
plot_result.result_nbd Plot the time series and change-points
plot_result.result_no_nbd Plot the time series and change-points
sim_hdchange_nbd Simulate data with neighbourhood
sim_hdchange_no_nbd Simulate data without neighbourhood
summary.result_nbd Summarize the estimation results
summary.result_no_nbd Summarize the estimation results
test_existence Test the existence of change-points in the data
ts_hdchange 'no_nbd' or 'nbd' object construction