Working with Dynamic Crop Models: Methods, Tools, and Examples for Agriculture and Environment (Hardcover, 2)

Section I Basics 1. Basics of Agricultural System Models 2. Statistical notions useful for modeling 3. The R programming language and software 4. Simulation with dynamic system models

Section II Methods 5. Uncertainty and sensitivity analysis 6. Parameter estimation with classical methods 7. Bayesian methods for parameter estimation 8. Data assimilation for dynamic models 9. Model evaluation 10. Putting it all together in a case study

Appendices 1. Model descriptions 2. An overview of the R package ZeBook