Promotional Information

Detailed explanations and descriptions of methods for working with dynamic system models in crop and agricultural sciences, including real-world examples and computer code

Table of Contents

Section I Basics1. Basics of Agricultural System Models2. Statistical notions useful for modeling3. The R programming language and software4. Simulation with dynamic system models

Section II Methods5. Uncertainty and sensitivity analysis6. Parameter estimation with classical methods7. Bayesian methods for parameter estimation8. Data assimilation for dynamic models9. Model evaluation10. Putting it all together in a case study

Appendices1. Model descriptions2. An overview of the R package ZeBook

About the Author

Daniel Wallach focuses on the application of statistical methods of dynamic systems, specifically on agronomy models. He has published in Agriculture, Ecosystems and Environment; Journal of Agricultural, Biological and Environmental Statistics and European Journal of Agronomy. David Makowski is an expert with the European Food Safety authority and the French Agency for Food, Environmental and Occupational Health and Safety and has authored 50 refereed articles and 10 book chapters on statistics, agricultural modeling and risk analysis. James Jones has authored more than 250 refereed scientific journal articles, developed and teached a graduate course based mostly on this book. He is a Fellow of the American Society of Agricultural and Biological Engineers, Fellow of the American Society of Agronomy, Fellow of the Soil Science Society of America and serves on several international science advisory committees related to agriculture and climate. Francois Brun specializes in agricultural modeling systems using the R language, and has published in Journal of Experimental Botany.

Reviews

"This edition adds chapters on the basics of dynamic system models, statistics, and simulation; examples of how the methods can be applied to real-world problems; advanced methods for parameter estimation, model evaluation, and data assimilation; a new chapter on how the topics fit together in a complete modeling project; and information on how to use the R language and platform." --ProtoView.com, April 2014