Introduction | Background information | Installing APSIM (Next Generation) | R functions for APSIM (Next Generation) | R functions for APSIM 'Classic' (7.x) - Only for Windows | Using 'apsimx' | Running a built-in example with 'apsimx_example' | Inspecting a file with 'inspect_apsimx': Why? | Inspecting and Editing the 'Maize' example | Proposed workflow | Wheat Example (APSIM-X) | Millet example (APSIM 'Classic') | Advanced Examples | Inspecting a 'Replacement' component | Editing a 'Replacement' | Inspecting and editing a Factorial | APSIM Inputs: Weather and Soil | Obtaining weather data | Obtaining soil data | File Type (or File Format) Details | Additional miscellaneous functions | Appendix

Nonlinear Regression | Index of self starting functions | Functions in 'base' R | Functions in this package (nlraa) | Documentation | References | List of available SS (self-start) functions. | Prediction, Simulation and Bootstrap | Datasets | What to do when convergence fails? | Some common error messages | Barley example | Other modeling approaches | Contributed packages | FlexParamCurve package | sicegar package | drc package | investr | easynls pacakge | chngpt pacakge | mcp package | nlsr package | propagate package | car package | HydroMe package | Nonlinear mixed models packages | Additional material on growth models

Bootstrapping | Nonlinear models | Simple example | Confidence interval for model parameters | Bootstrapping generalized nonlinear models | Bootstrapping nonlinear mixed models | Confidence bands for generalized nonlinear models | Simulation | Fitted values | Prediction | Appendix | Note on simulate methodology | References

Writing scripts and running APSIM-X at the command line | Windows | Unix (Mac) or Linux (Debian) | Pre Sep 2021 (mono required) | Functions in the apsimx package | Unix and Windows paths | Session information | Links

Introduction | optim_apsim | optim_apsimx | Wheat Example | Observed data | Before optimization | Setting up the optimization | Running the optimization | Multi-simulation optimization | Additional considerations and potential issues

Introduction | Uncertainty Analysis using for loops | sens_apsimx | Example using sens_apsimx | Creating grids | First option: parameterSets | Second option: Morris

Motivation | Confidence and Prediciton Bands in Regression | Linear Example | Nonlinear Example: Loblolly | Nonlinear Example: Puromycin | Nonlinear Example: Maize Leaf Extension Rate | Nonlinear Example: Theoph | Nonlinear Example: Prediction bands for an observation within a subject | Nonlinear Example: Prediction bands for an mean function (new subject) | References

Intro | Linear Model | Generalized least squares (gls)

Introduction | Example