Working with dynamic crop models [recurso electrónico] : methods, tools and examples for agriculture and environment / [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun.
Tipo de material: TextoEditor: London : Academic Press/Elsevier Science, [2014]Edición: Second editionDescripción: 1 online resource (xvi, 487 pages) : illustrationsTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 1306195659; 9781306195652; 9780444594464; 0444594469Tema(s): Crop yields -- Mathematical models | Crops -- Growth -- Mathematical models | Agricultural mathematics | Crop yields | Crops -- Growth -- Statistical methods | TECHNOLOGY & ENGINEERING -- Agriculture -- General | Crop yields -- Mathematical models | Crops -- Growth -- Mathematical modelsGénero/Forma: Electronic books.Formatos físicos adicionales: Print version:: Working with dynamic crop models.Clasificación CDD: 631.5 | 631.5/8/015118 | 631.58015118 Clasificación LoC:SB112.5Recursos en línea: Libro electrónico ScienceDirectTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | SB112.5 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 380125-2001 |
Includes bibliographical references and index.
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.
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.
Print version record.
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