Introduction | 1. Input Data Schemas and Ensemble Representation | Model Ensemble Output (EFI Long Format) | Observation Dataset | 2. Statistical Error Model and Fixture Generation | R Simulation Code (Reference) | 3. Data Intake, Reshaping, and Alignment | Reshaping Ensemble Data to Matrix (ens_mat) | Temporal Alignment (align_by_time) | 4. Metric Calculations and Interpretation | Comparing Calculated Metrics against Theoretical Expectations | 5. Visualizations and Automated Reporting | Spaghetti + Ribbon Timeseries Plot (metric_timeseries_plot) | Diagnostic Scatter Plot (metric_scatter_plot) | Residual Plot (metric_residual_plot) | 6. Substituting Custom Processed Data & Real-World EFI Example

install package from Github | Define species groups | Run the Bayesian allometry model | Predict for individual trees | Predict for a stand

Introduction | Install package from Github | Load library and example data | run QA/QC checks | Merge data into one data frame | Fit FvCB model to composite data | Refit with leaf-level random effects | Fitting the model with covariates | Citations