Wallach, Daniel autor text -us 2014 2a edición monographic eng xvi, 487 páginas : ilustraciones, gráficas, tablas 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. Preface -- Section 1: Basics -- Chapter 1. Basics of Agricultural System Models -- 1 Introduction -- 2 System Models -- 3 Developing Dynamic System Models -- 4 Other Forms of System Models -- 5 Examples of Dynamic Agricultural System Models -- Exercises -- References -- Chapter 2. Statistical Notions Useful for Modeling -- 1 Introduction -- 2 Random Variable -- 3 The Probability Distribution of a Random Variable -- 4 Several Random Variables -- 5 Samples, Estimators, and Estimates -- 6 Regression Models -- 7 Bayesian Statistics -- Exercises -- References -- Chapter 3. The R Programming Language and Software -- 1 Introduction -- 2 Getting Started -- 3 Objects in R -- 4 Vectors (numerical, logical, character) -- 5 Other Data Structures -- 6 Read from and Write to File System -- 7 Control Structures -- 8 Functions -- 9 Graphics -- 10 Statistics and Probability -- 11 Advanced Data Processing -- 12 Additional Packages (libraries) -- 13 Running an External Model from R -- 14 Reducing Computing Time -- Exercises -- References -- Chapter 4. Simulation with Dynamic System Models -- 1 Introduction -- 2 Simulating Continuous Time Models (differential equation form) -- 3 Simulation of System Models in Difference Equation Form -- Exercises -- References -- Section 2: Methods -- Chapter 5. Uncertainty and Sensitivity Analysis -- 1 Introduction -- 2 A Simple Example using Uncertainty and Sensitivity Analysis -- 3 Uncertainty Analysis -- 4 Sensitivity Analysis -- 5 Recommendations -- 6 R code Used in this Chapter -- Exercises -- References -- Chapter 6. Parameter Estimation with Classical Methods (Model Calibration) -- 1 Introduction -- 2 An Overview of Model Calibration -- 3 The Statistics of Parameter Estimation -- 4 Application of Statistical Principles to System Models -- 5 Algorithms for OLS -- 6 R Functions for Parameter Estimation -- Exercises -- Models for Exercises -- References -- Chapter 7. Parameter Estimation with Bayesian Methods -- 1 Introduction -- 2 Ingredients for Implementing a Bayesian Estimation Method -- 3 Computation of Posterior Mode -- 4 Algorithms for Estimating Posterior Probability Distribution -- 5 Concluding Remarks -- Exercises -- References -- Chapter 8. Data Assimilation for Dynamic Models -- 1 Introduction -- 2 Model Specification -- 3 Filter and Smoother for Gaussian Dynamic Linear Models -- 4 Filter and Smoother for Non-Linear Models -- 5 Concluding Remarks -- Exercises -- References -- Chapter 9. Model Evaluation -- 1 Introduction -- 2 A Model as a Scientific Hypothesis -- 3 Comparing Simulated and Observed Values -- 4 From the Sample to the Population -- 5 The Predictive Quality of a Model -- 6 Summary -- 7 R Functions -- Exercises -- References -- Chapter 10. Putting It All Together in a Case Study -- 1 Introduction -- 2 Description of the Case Study -- 3 How Difficult and Time-Consuming is Each Step? -- 4 R Code Used in This Chapter -- Appendix 1. The Models Included in the ZeBook R Package: Description, R Code, and Examples of Results -- 1 Introduction -- 2 SeedWeight Model -- 3 Magarey Model -- 4 Soil Carbon Model -- 5 WaterBalance Model -- 6 Maize Crop Model -- 7 Verhulst Model -- 8 Population Age Model -- 9 Predator-Prey Model -- 10 Weed Model -- 11 EPIRICE Model -- References -- Appendix 2. An Overview of the R Package ZeBook -- 1 Introduction -- 2 Installation -- 3 Functions and Demos in the Zebook Package -- 4 How to use the ZeBook Package -- 5 List of Packages Needed -- Index specialized Daniel Wallach...[y otros] Incluye bibliografías Crop yields Mathematical models Crops Growth Mathematical models Cultivos Crecimiento Modelos matemáticos Rendimiento de los cultivos Modelos matemáticos SB112.5 .W67 2014 631.558 W67 2014 978-0-12-397008-4 178527 mxchpua 220117 20230317134601.0 dia_7323