Feature selection, Random Forest, and SEM workflow for simulated stand dataset

This dataset and R script provide the workflow for analyzing stand structure and productivity of Chinese fir (<i>Cunninghamia lanceolata</i>) stands using simulated data. The dataset includes key stand, site, and climate variables. The R script demonstrates the following steps:Feature selection with the Boruta algorithmRandom Forest modeling with cross-validation and stepwise variable eliminationMulticollinearity diagnostics using VIFStructural Equation Modeling (SEM) and effect decomposition with <code>piecewiseSEM</code> and <code>semEff</code><b>Notes</b>The dataset is simulated for reproducibility and does not include raw inventory data.Users may adapt the script to their own datasets for similar analyses in forestry and ecology.