http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
methods, tools and examples for agriculture and environment
1 online resource (xvi, 487 pages) : illustrations
This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines.
1. Basics of agricultural system models -- 2. Statistical notions useful for modeling -- 3. The R programming language software -- 4. Simulation with dynamic system models -- 5. Uncertainty and sensitivity analysis -- 6. Parameter estimation with classical methods (model calibration) -- 7. Parameter estimation with Bayesian methods -- 8. Data assimilation for dynamic models -- 9. Model evaluation -- 10. Putting it all together in a case study.
[edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun.
Includes bibliographical references and index.