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    1. Naturvetenskap och teknik
    2. Teknik och industri
    3. Agronomi och lantbruk

    Working with Dynamic Crop Models

    Methods, Tools and Examples for Agriculture and Environment

    AvDaniel Wallach,David Makowski

    Inbunden, Engelska, 2018

    1 436 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Fler format och utgåvor

    Inbunden

    1 208 kr

    Beskrivning

    Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, 3e, is a complete guide to working with dynamic system models, with emphasis on models in agronomy and environmental science. The introductory section presents the foundational information for the book including the basics of system models, simulation, the R programming language, and the statistical notions necessary for working with system models. The most important methods of working with dynamic system models, namely uncertainty and sensitivity analysis, model calibration (frequentist and Bayesian), model evaluation, and data assimilation are all treated in detail, in individual chapters.

    New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling.

    The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems.



    • An expanded introductory section presents the basics of dynamic system modeling, with numerous examples from multiple fields, plus chapters on numerical simulation, statistics for modelers, and the R language
    • Covers in detail the basic methods: uncertainty and sensitivity analysis, model calibration (both frequentist and Bayesian), model evaluation, and data assimilation
    • Every method chapter has numerous examples of applications based on real problems, as well as detailed instructions for applying the methods to new problems using R
    • Each chapter has multiple exercises for self-testing or for classroom use
    • An R package with much of the code from the book can be freely downloaded from the CRAN package repository

    Produktinformation

    • Utgivningsdatum:2018-09-28
    • Mått:152 x 229 x undefined mm
    • Vikt:1 260 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:613
    • Upplaga:3
    • Förlag:Elsevier Science
    • ISBN:9780128117569

    Utforska kategorier

    • Agronomi och lantbruk inom Naturvetenskap och teknik
    • Lantbruksteknik inom Naturvetenskap och teknik
    • Agronomi inom Naturvetenskap och teknik

    Mer om författaren

    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.

    Innehållsförteckning

    • Section A Background1. Basics of Agricultural System Models2. The R Programming Language and Software3. Simulation with Dynamic System Models4. Statistical Notions Useful for Modeling5. Regression Analysis, FrequentistSection B Basic methods6. Uncertainty and Sensitivity Analysis7. Calibration of System Models8. Parameter Estimation With Bayesian Methods9. Model Evaluation10. Putting It All Together in a Case StudySection C Advanced Methods11. Metamodeling12. Multimodel Ensembles13. Gene-Based Crop Models14. Data Assimilation for Dynamic Models15. Models as an Aid to SamplingAppendix 1:   The Models Included in the ZeBook R Package: Description, R Code, and Examples of ResultsAppendix 2:  An Overview of the R Package ZeBook