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.