R: Change Point Detection for Non-Stationary and Cross-Correlated Time Series

# Change Point Detection for Non-Stationary and Cross-Correlated Time Series

## Documentation for package ‘FluxPoint’ version 0.1.2

- DESCRIPTION file
- Package NEWS

## Help Pages

add_jumps | Add mean shifts to multivariate time series data
estimatePhinu_nondiag | Estimate non-diagonal VAR(1) parameters after mean removal
estimate_musseg | Estimate fluctuating mean segmentwise given detected change points
estimate_RWVAR_cp_heter | Robust parameter estimation (RPE) for multivariate time series
FluxPoint | FluxPoint change point detection algorithm
FluxPoint_raw | Core change point detection algorithm (given known parameters)
generate_data | Generate multivariate time series from the proposed model
get_metrics | Evaluate change point detection accuracy metrics
get_Sigs | Compute the covariance matrix Sigma_{\mathrm{ALL}}^* for observations within a moving window
get_Sig_e1_approx | Approximate the long-run covariance matrix Gamma_{\boldsymbol{epsilon}}(0)
plot_FluxPoint | Plot multivariate time series with detected change points and estimated means
random_Phi | Randomly generate an autoregressive coefficient matrix Phi
random_Signu | Randomly generate an innovation covariance matrix Sigma_{\boldsymbol{nu}}