The Resource Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book)
Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book)
Resource Information
The item Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- 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 programmi
- Language
- eng
- Edition
- Second edition.
- Extent
- 1 online resource (xvi, 487 pages)
- Note
- 6 Read from and Write to File System
- Contents
-
- Front Cover; Working with Dynamic Crop Models; Copyright Page; Contents; Preface; 1 Basics; 1 Basics of Agricultural System Models; 1 Introduction; 2 System Models; 2.1 Systems Approach; 2.2 System Environment and Boundary; 2.3 System Model and Simulation; 2.3.1 System Model; 2.3.2 Simulation; 2.3.3 General Form of a Dynamic System Model; 2.4 State Variables U(t); 2.5 Explanatory Variables and Parameters; 3 Developing Dynamic System Models; 3.1 Methods; 3.2 Example Development of a System Model; 4 Other Forms of System Models; 4.1 Random Elements in Dynamic Equations
- 4.2 A Dynamic System Model as a Response Model4.2.1 Random Elements in System Response Equations; 5 Examples of Dynamic Agricultural System Models; 5.1 Simple Maize Crop Model; 5.2 Dynamic Soil Water Model and Drought Index; 5.2.1 The ARID Soil Water Model; 5.2.2 Combining Soil and Crop Models; 5.2.3 Extending the Soil Water Model for Non-Homogenous Soils; 5.3 Population Dynamics Models; 5.3.1 Homogenous Population with Limited Food Supply; 5.3.2 Population Dynamics Model with Age Classes; 5.3.3 Predator-Prey Population Dynamics Model; 5.3.4 Modeling Spatial Variations in Population Dynamics
- ExercisesEasy; Moderate; Difficult; References; 2 Statistical Notions Useful for Modeling; 1 Introduction; 1.1 In This Chapter; 2 Random Variable; 3 The Probability Distribution of a Random Variable; 3.1 Cumulative Distribution and Density Functions; 3.2 Expectation, Variance, and Quantiles of a Random Variable; 3.3 Best Predictor of Y Using a Constant; 3.4 Particular Distributions; 4 Several Random Variables; 4.1 Joint Distribution; 4.2 Marginal Distribution; 4.3 Conditional Distribution and Independence; 4.4 Covariance and Correlation
- 4.5 Expectation and Variance for Multiple Random Variables4.6 Best Predictor of Y Using a Function of X; 4.7 The Multivariate Normal Distribution; 5 Samples, Estimators, and Estimates; 5.1 Simple Random Samples; 5.2 Sampling in Agronomy; 5.3 Estimators and Estimates; 5.4 Effective Sample Size; 6 Regression Models; 7 Bayesian Statistics; 7.1 The Difference Between Bayesian and Frequentist Statistics; 7.2 Basic Ideas of Bayesian Statistics; 7.3 Bayesian Parameter Estimation in Modeling; 7.4 Frequentist or Bayesian?; Exercises; References; 3 The R Programming Language and Software
- 1 Introduction1.1 What Is R?; 1.2 Why R?; 1.3 What's in This Chapter?; 2 Getting Started; 2.1 How to Install the R Software; 2.2 The R Interface; 2.3 Notation for R Code; 2.4 Using R as a Simple Calculator; 2.5 Using a Script Editor; 2.6 The Notion of an R Program; 2.7 Debugging an R Program; 2.8 Need Help?; 3 Objects in R; 3.1 Creating Objects; 3.2 Types of Objects; 4 Vectors (numerical, logical, character); 4.1 Creation of a Vector; 4.2 Subscripting a Vector; 4.3 Operations on Vectors; 4.4 Combining Vectors; 5 Other Data Structures; 5.1 Matrices; 5.2 Data Frames; 5.3 Lists
- Isbn
- 9780444594464
- Label
- Working with dynamic crop models : methods, tools and examples for agriculture and environment
- Title
- Working with dynamic crop models
- Title remainder
- methods, tools and examples for agriculture and environment
- Statement of responsibility
- [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun
- Language
- eng
- Summary
- 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 programmi
- Cataloging source
- EBLCP
- Dewey number
-
- 631.5
- 631.5/8/015118
- 631.58015118
- Illustrations
- illustrations
- Index
- index present
- LC call number
- SB112.5
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorDate
-
- 1942-
- 1972-
- 1944-
- http://library.link/vocab/relatedWorkOrContributorName
-
- Wallach, Daniel
- Makowski, David
- Jones, James Wigington
- Brun, François
- http://library.link/vocab/subjectName
-
- Crop yields
- Crops
- Agricultural mathematics
- Crop yields
- Crop yields
- Crop yields
- Crops
- Crops
- TECHNOLOGY & ENGINEERING / Agriculture / General
- Label
- Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book)
- Note
- 6 Read from and Write to File System
- Bibliography note
- Includes bibliographical references and index
- Contents
-
- Front Cover; Working with Dynamic Crop Models; Copyright Page; Contents; Preface; 1 Basics; 1 Basics of Agricultural System Models; 1 Introduction; 2 System Models; 2.1 Systems Approach; 2.2 System Environment and Boundary; 2.3 System Model and Simulation; 2.3.1 System Model; 2.3.2 Simulation; 2.3.3 General Form of a Dynamic System Model; 2.4 State Variables U(t); 2.5 Explanatory Variables and Parameters; 3 Developing Dynamic System Models; 3.1 Methods; 3.2 Example Development of a System Model; 4 Other Forms of System Models; 4.1 Random Elements in Dynamic Equations
- 4.2 A Dynamic System Model as a Response Model4.2.1 Random Elements in System Response Equations; 5 Examples of Dynamic Agricultural System Models; 5.1 Simple Maize Crop Model; 5.2 Dynamic Soil Water Model and Drought Index; 5.2.1 The ARID Soil Water Model; 5.2.2 Combining Soil and Crop Models; 5.2.3 Extending the Soil Water Model for Non-Homogenous Soils; 5.3 Population Dynamics Models; 5.3.1 Homogenous Population with Limited Food Supply; 5.3.2 Population Dynamics Model with Age Classes; 5.3.3 Predator-Prey Population Dynamics Model; 5.3.4 Modeling Spatial Variations in Population Dynamics
- ExercisesEasy; Moderate; Difficult; References; 2 Statistical Notions Useful for Modeling; 1 Introduction; 1.1 In This Chapter; 2 Random Variable; 3 The Probability Distribution of a Random Variable; 3.1 Cumulative Distribution and Density Functions; 3.2 Expectation, Variance, and Quantiles of a Random Variable; 3.3 Best Predictor of Y Using a Constant; 3.4 Particular Distributions; 4 Several Random Variables; 4.1 Joint Distribution; 4.2 Marginal Distribution; 4.3 Conditional Distribution and Independence; 4.4 Covariance and Correlation
- 4.5 Expectation and Variance for Multiple Random Variables4.6 Best Predictor of Y Using a Function of X; 4.7 The Multivariate Normal Distribution; 5 Samples, Estimators, and Estimates; 5.1 Simple Random Samples; 5.2 Sampling in Agronomy; 5.3 Estimators and Estimates; 5.4 Effective Sample Size; 6 Regression Models; 7 Bayesian Statistics; 7.1 The Difference Between Bayesian and Frequentist Statistics; 7.2 Basic Ideas of Bayesian Statistics; 7.3 Bayesian Parameter Estimation in Modeling; 7.4 Frequentist or Bayesian?; Exercises; References; 3 The R Programming Language and Software
- 1 Introduction1.1 What Is R?; 1.2 Why R?; 1.3 What's in This Chapter?; 2 Getting Started; 2.1 How to Install the R Software; 2.2 The R Interface; 2.3 Notation for R Code; 2.4 Using R as a Simple Calculator; 2.5 Using a Script Editor; 2.6 The Notion of an R Program; 2.7 Debugging an R Program; 2.8 Need Help?; 3 Objects in R; 3.1 Creating Objects; 3.2 Types of Objects; 4 Vectors (numerical, logical, character); 4.1 Creation of a Vector; 4.2 Subscripting a Vector; 4.3 Operations on Vectors; 4.4 Combining Vectors; 5 Other Data Structures; 5.1 Matrices; 5.2 Data Frames; 5.3 Lists
- Control code
- SCIDI865335096
- Dimensions
- unknown
- Edition
- Second edition.
- Extent
- 1 online resource (xvi, 487 pages)
- Form of item
- online
- Isbn
- 9780444594464
- Other physical details
- illustrations
- Specific material designation
- remote
- Label
- Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book)
- Note
- 6 Read from and Write to File System
- Bibliography note
- Includes bibliographical references and index
- Contents
-
- Front Cover; Working with Dynamic Crop Models; Copyright Page; Contents; Preface; 1 Basics; 1 Basics of Agricultural System Models; 1 Introduction; 2 System Models; 2.1 Systems Approach; 2.2 System Environment and Boundary; 2.3 System Model and Simulation; 2.3.1 System Model; 2.3.2 Simulation; 2.3.3 General Form of a Dynamic System Model; 2.4 State Variables U(t); 2.5 Explanatory Variables and Parameters; 3 Developing Dynamic System Models; 3.1 Methods; 3.2 Example Development of a System Model; 4 Other Forms of System Models; 4.1 Random Elements in Dynamic Equations
- 4.2 A Dynamic System Model as a Response Model4.2.1 Random Elements in System Response Equations; 5 Examples of Dynamic Agricultural System Models; 5.1 Simple Maize Crop Model; 5.2 Dynamic Soil Water Model and Drought Index; 5.2.1 The ARID Soil Water Model; 5.2.2 Combining Soil and Crop Models; 5.2.3 Extending the Soil Water Model for Non-Homogenous Soils; 5.3 Population Dynamics Models; 5.3.1 Homogenous Population with Limited Food Supply; 5.3.2 Population Dynamics Model with Age Classes; 5.3.3 Predator-Prey Population Dynamics Model; 5.3.4 Modeling Spatial Variations in Population Dynamics
- ExercisesEasy; Moderate; Difficult; References; 2 Statistical Notions Useful for Modeling; 1 Introduction; 1.1 In This Chapter; 2 Random Variable; 3 The Probability Distribution of a Random Variable; 3.1 Cumulative Distribution and Density Functions; 3.2 Expectation, Variance, and Quantiles of a Random Variable; 3.3 Best Predictor of Y Using a Constant; 3.4 Particular Distributions; 4 Several Random Variables; 4.1 Joint Distribution; 4.2 Marginal Distribution; 4.3 Conditional Distribution and Independence; 4.4 Covariance and Correlation
- 4.5 Expectation and Variance for Multiple Random Variables4.6 Best Predictor of Y Using a Function of X; 4.7 The Multivariate Normal Distribution; 5 Samples, Estimators, and Estimates; 5.1 Simple Random Samples; 5.2 Sampling in Agronomy; 5.3 Estimators and Estimates; 5.4 Effective Sample Size; 6 Regression Models; 7 Bayesian Statistics; 7.1 The Difference Between Bayesian and Frequentist Statistics; 7.2 Basic Ideas of Bayesian Statistics; 7.3 Bayesian Parameter Estimation in Modeling; 7.4 Frequentist or Bayesian?; Exercises; References; 3 The R Programming Language and Software
- 1 Introduction1.1 What Is R?; 1.2 Why R?; 1.3 What's in This Chapter?; 2 Getting Started; 2.1 How to Install the R Software; 2.2 The R Interface; 2.3 Notation for R Code; 2.4 Using R as a Simple Calculator; 2.5 Using a Script Editor; 2.6 The Notion of an R Program; 2.7 Debugging an R Program; 2.8 Need Help?; 3 Objects in R; 3.1 Creating Objects; 3.2 Types of Objects; 4 Vectors (numerical, logical, character); 4.1 Creation of a Vector; 4.2 Subscripting a Vector; 4.3 Operations on Vectors; 4.4 Combining Vectors; 5 Other Data Structures; 5.1 Matrices; 5.2 Data Frames; 5.3 Lists
- Control code
- SCIDI865335096
- Dimensions
- unknown
- Edition
- Second edition.
- Extent
- 1 online resource (xvi, 487 pages)
- Form of item
- online
- Isbn
- 9780444594464
- Other physical details
- illustrations
- Specific material designation
- remote
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Working-with-dynamic-crop-models--methods-tools/nv-g-vcP4zM/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Working-with-dynamic-crop-models--methods-tools/nv-g-vcP4zM/">Working with dynamic crop models : methods, tools and examples for agriculture and environment, [edited by] Daniel Wallach, David Makowski, James W. Jones, Francois Brun, (electronic book)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
