la_abs_bias_metric      Calculate absolute bias
la_add_equation_to_results
                        Add equation information to a results table
la_bias                 Calculate prediction bias
la_build_equation       Build a readable equation from a fitted model
la_ccc                  Calculate Lin's concordance correlation
                        coefficient
la_create_derived       Create derived leaf parameters
la_d                    Calculate Willmott's index of agreement
la_descriptive_default
                        Summarize the default leaf area variables
la_descriptive_stats    Calculate descriptive statistics for selected
                        variables
la_evaluate_linear_models
                        Evaluate all linear models from a
                        'la_fit_linear_models()' object
la_evaluate_mixed_models
                        Evaluate all mixed models from a
                        'la_fit_mixed_models()' object
la_evaluate_model       Evaluate a single fitted model
la_evaluate_nonlinear_models
                        Evaluate all nonlinear models from a
                        'la_fit_nonlinear_models()' object
la_extract_coefficients
                        Extract model coefficients
la_feature_display_names
                        Display labels for leaf variables
la_feature_labels       Display labels for leaf variables
la_fit_linear_models    Fit candidate linear models for leaf area
                        estimation
la_fit_mixed_models     Fit candidate linear mixed-effects models for
                        leaf area estimation
la_fit_nonlinear_models
                        Fit multiple nonlinear models
la_input_overview       Summarize a validated leaf area dataset
la_linear_fitted_values
                        Extract fitted values from linear model results
la_linear_formulas      List default linear model formulas
la_list_derived         List available derived variables
la_mae                  Calculate mean absolute error
la_mape                 Calculate mean absolute percentage error
la_matrixplot           Create a matrix plot for selected variables
la_matrixplot_default   Create a default matrix plot for leaf variables
la_metric_table         Calculate a standard metric table from observed
                        and predicted values
la_mixed_coefficients   Extract coefficients from a mixed model
la_mixed_fitted_values
                        Extract fitted values from mixed-model results
la_mixed_formulas       List default mixed-model formulas
la_mse                  Calculate mean squared error
la_nonlinear_coefficients
                        Return coefficients from a selected nonlinear
                        model
la_nonlinear_fitted_values
                        Extract observed, fitted values and residuals
                        for a selected nonlinear model
la_nonlinear_specs      Default nonlinear model specifications
la_nse                  Calculate Nash-Sutcliffe efficiency
la_plot_observed_predicted
                        Observed versus predicted leaf area plot
la_plot_residual_histogram
                        Histogram of residuals
la_plot_residual_qq     QQ plot of residuals
la_plot_residuals       Residuals versus fitted values plot
la_plot_scatter         Scatter plot between two selected variables
la_plot_scatter_set     Scatter plots for multiple selected predictors
                        against leaf area
la_predict_from_results
                        Predict using one selected model from a fit
                        object
la_predict_linear_model
                        Predict from a linear model
la_predict_mixed_model
                        Predict from a mixed model
la_predict_model        Predict from a fitted model
la_predict_nonlinear_model
                        Predict from a nonlinear model
la_predict_top_ranked   Predict from the top-ranked model
la_r                    Calculate Pearson correlation coefficient
la_r_squared            Calculate coefficient of determination
la_rank_models          Rank models using a simple metric priority rule
la_rank_models_by_metrics
                        Rank models by average metric positions
la_rank_models_weighted
                        Rank models using a weighted score
la_rmse                 Calculate root mean squared error
la_top_models           Select the top models from a ranking table
la_validate_input       Validate and standardize input data for leaf
                        area analysis
leafarea_sample         Example dataset for leaf area modeling
run_leafareaR_app       Launch the built-in Shiny application
