R: Deep Learning–Based Changepoint Detection with Local Neural Models

# Deep Learning–Based Changepoint Detection with Local Neural Models

## Documentation for package ‘scanCP’ version 0.1.0

- DESCRIPTION file
- Package README

## Help Pages

best_split_free | Best Split for Binary Labels (Free Assignment)
calc_detector | Compute the MLP-Based Changepoint Detector Statistic
combine_detectors | Combine Multiple Detector Statistics into a Joint Detector
decompose_signal_core | Core Signal Decomposition (Changepoints + Piecewise Correction)
detect_cp_ecdf | ECDF-Based Changepoint Detection for a Detector Statistic
fit_global_mlp | Fit Global MLP and Compute Residual Diagnostics
fit_mlp | Fit Rolling MLP Models for Change Point Detection
ma | Two-Sided Moving Average Smoothing
plot_mlp_fits_interactive | Interactive Plot of Rolling MLP Fits
scan_cp | Full Changepoint Detection Pipeline Using Rolling MLPs
scan_cp_multi_async | Asynchronous Multivariate Changepoint Detection
scan_cp_multi_sync | Multivariate Synchronized Changepoint Detection
select_best_spike | Select the Most Significant Spike in an ECDF Spacing Curve
simulate_piecewise_signal_idx | Simulate a Piecewise-Constant Signal with Smooth Trend and Noise