# NRMstatsML News

## NRMstatsML 0.1.0 (initial release)

### New features

* **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*.
