| add_climate | Attach a covariate layer to a project |
| add_layer | Attach a covariate layer to a project |
| add_satellite | Attach a covariate layer to a project |
| add_soil | Attach a covariate layer to a project |
| agri_project | Create an agricultural analysis project |
| build_features | Build the model design matrix |
| check_project | Check a project for the faults that invalidate an analysis |
| crop_parameters | Indicative crop thermal parameters |
| demo_agri_data | A demonstration agricultural data set |
| explain | Explain a fitted model |
| explain.agri_model | Explain a fitted model |
| growing_degree_days | Growing degree days |
| list_learners | List registered sources and learners |
| list_sources | List registered sources and learners |
| phenology_windows | Derive phenological windows from accumulated thermal time |
| plot.agri_model | Plot a fitted model |
| plot.agri_project | Plot a project's management units |
| plot.agri_resample | Plot a resampling scheme |
| plot_effect | Plot a marginal effect |
| plot_map | Map predictions, residuals or uncertainty |
| plot_uncertainty | Plot prediction intervals and their coverage |
| predict.agri_model | Predict from a fitted model |
| provenance | Accessors for project components |
| register_learner | Register a learning algorithm |
| register_source | Register a covariate source |
| report | Write a model card |
| report.agri_model | Write a model card |
| resample_scheme | Build a resampling scheme |
| seasons_of | Accessors for project components |
| stack_weights | Stack weights from a fitted ensemble |
| train_model | Train and honestly validate a model |
| uncertainty | Prediction intervals by split conformal inference |
| uncertainty.agri_model | Prediction intervals by split conformal inference |
| units_of | Accessors for project components |