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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.