trendML module: nrm_trend(), nrm_mann_kendall(), nrm_sens_slope(),
nrm_structural_break() — non-parametric trend detection and Bai-Perron
structural break analysis.
multiSysML module: nrm_multivariate(), nrm_pls(), nrm_sem() —
scaled OLS, Partial Least Squares, and Structural Equation Modelling.
responseML module: nrm_response_curve() (quadratic, linear, and
Mitscherlich types) and nrm_optimize_input() for economic optimum
calculation.
tsML module: nrm_arima() and nrm_forecast() wrapping
forecast::auto.arima() with 95 % prediction intervals.
panelML module: nrm_panel() (fixed/random effects with Hausman test)
and nrm_did() (Difference-in-Differences).
uncertaintyML module: nrm_bootstrap(), nrm_monte_carlo(), and
unified nrm_uncertainty() dispatcher.
autoML module: nrm_automl() for automated cross-validated model
selection and nrm_benchmark() for hold-out evaluation.
Generic helpers: nrm_data_check(), nrm_summary(), nrm_plot().
Example dataset nrm_example: 20-year synthetic NRM time series.
Vignette: Getting Started with NRMstatsML.