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Karline Soetaert Jeff Cash - Solving Differential Equations in R

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Karline Soetaert Jeff Cash Solving Differential Equations in R

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Solving Differential Equations in R; Preface; R as a Problem Solving Environment; About the Three Authors; Acknowledgment; References; Contents; Chapter 1 Differential Equations; 1.1 Basic Theory of Ordinary Differential Equations; 1.1.1 First Order Differential Equations; 1.1.2 Analytic and Numerical Solutions; 1.1.3 Higher Order Ordinary Differential Equations; 1.1.4 Initial and Boundary Values; 1.1.5 Existence and Uniqueness of Analytic Solutions; 1.2 Numerical Methods; 1.2.1 The Euler Method; 1.2.2 Implicit Methods; 1.2.3 Accuracy and Convergence of Numerical Methods.;Mathematics plays an important role in many scientific and engineering disciplines. This book deals with the numerical solution of differential equations, a very important branch of mathematics. Our aim is to give a practical and theoretical account of how to solve a large variety of differential equations, comprising ordinary differential equations, initial value problems and boundary value problems, differential algebraic equations, partial differential equations and delay differential equations. The solution of differential equations using R is the main focus of this book. It is therefore intended for the practitioner, the student and the scientist, who wants to know how to use R for solving differential equations. However, it has been our goal that non-mathematicians should at least understand the basics of the methods, while obtaining entrance into the relevant literature that provides more mathematical background. Therefore, each chapter that deals with R examples is preceded by a chapter where the theory behind the numerical methods being used is introduced. In the sections that deal with the use of R for solving differential equations, we have taken examples from a variety of disciplines, including biology, chemistry, physics, pharmacokinetics. Many examples are well-known test examples, used frequently in the field of numerical analysis.

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Karline Soetaert , Jeff Cash and Francesca Mazzia Use R! Solving Differential Equations in R 2012 10.1007/978-3-642-28070-2_1 Springer-Verlag Berlin Heidelberg 2012
1. Differential Equations
Karline Soetaert 1, Jeff Cash 2 and Francesca Mazzia 3
(1)
Department Ecosystem Studies, Royal Netherlands Institute for Sea Research, Yerseke, The Netherlands
(2)
Mathematics, Imperial College, South Kensington Campus, London, UK
(3)
Dipartimento di Matematica, University of Bari, Bari, Italy
Abstract
Differential equations (DEs) occur in many branches of science and technology, and there is a real need to solve them both accurately and efficiently. There are relatively few problems for which an analytic solution can be found, so if we want to solve a large class of problems, then we need to resort to numerical calculations. In this chapter we will give a very brief survey of the theory behind DEs and their solution. We introduce concepts such as analytic and numerical methods, the order of differential equations, existence and uniqueness of solutions, implicit and explicit methods. We end with a brief survey of the different types of differential equations that will be dealt with in later chapters of this book.
1.1 Basic Theory of Ordinary Differential Equations
Although the material contained in this section is largely of a theoretical nature it is presented at a rather basic level and the reader is advised to at least skim through it.
1.1.1 First Order Differential Equations
The general form taken by a first order ordinary differential equation ( ODE ) is
Solving Differential Equations in R - image 1
(1.1)
which may also be written as
Solving Differential Equations in R - image 2
(1.2)
where f is a given function of x and y and y contained in Picture 3 is a vector. Here x is called the independent variable and y = y ( x ) is the dependent variable.
This equation is called first order as it contains no higher derivatives than the first. Furthermore, () is called an ordinary differential equation as y depends on one independent variable only.
1.1.2 Analytic and Numerical Solutions
A differentiable function y ( x ) is a solution of () if for all x
Solving Differential Equations in R - image 4
(1.3)
If we suppose that y ( x 0) is known, the solution of () with respect to x , to give:
Solving Differential Equations in R - image 5
(1.4)
In some cases this integral can be evaluated exactly to give an equation for y , and this is called an analytic solution. For example, the equation
Solving Differential Equations in R - image 6
(1.5)
has as analytic solution
Solving Differential Equations in R - image 7
(1.6)
Note the free parameter c that occurs in the solution. It has been known for a long time that the solution of a first order equation contains a free parameter and that this solution is uniquely defined if for example we impose an initial condition of the form Picture 8 and we suppose that the function f satisfies some regularity conditions. This is important and we will return to it later.
Unfortunately, it is true to say that many ordinary differential equations which appear to be quite harmless, in the sense that we could expect them to be easy to solve, cannot be solved analytically, i.e. the solution can not be expressed in terms of known functions. An illuminating example of this is given in [) is changed slightly to
Solving Differential Equations in R - image 9
(1.7)
then the solution has a very complex structure in terms of Airy functions [) numerically rather than analytically.
Undergraduate mathematics courses often give the impression that most differential equations can be solved analytically, with numerical techniques being developed to deal with those few classes of equations that have no analytic solution. In fact, the opposite is true: while an analytic solution is extremely useful if it does exist, experience shows that most equations of practical interest need to be solved numerically.
1.1.3 Higher Order Ordinary Differential Equations
In the previous section, we considered only the first order differential equation (). Ordinary differential equations can include higher order derivatives as well. For example, second order equations of the form:
Solving Differential Equations in R - image 10
(1.8)
arise in many practical applications.
Normally, in order to deal with the second order equation (), we first convert it to a system of first order equations. This we do by defining an extra dependent variable, which equals the first order derivative of y , in the following way:
Solving Differential Equations in R - image 11
(1.9)
Rather than having one differential equation, we now have a system of two differential equations. Defining Solving Differential Equations in R - image 12 , () we need to specify two conditions to define the solution uniquely in this second order case.
As a simple example consider a small stone falling through the air from a tower. Gravity produces an acceleration of Solving Differential Equations in R - image 13 , while the air exerts a resistive force which is proportional to the velocity ( v ). The differential equation describing this is:
Solving Differential Equations in R - image 14
(1.10)
If we are interested in the distance from the top of the tower ( x ), we use the fact that the velocity v = x , and the equation becomes a second order differential equation:
Solving Differential Equations in R - image 15
(1.11)
Now, in order to solve (), we rewrite it as two first order equations.
Solving Differential Equations in R - image 16
(1.12)
This technique carries over to higher order equations as well. If we are faced with the numerical solution of an n th order equation, it is often advisable to first reduce it to a system of n first order equations using the obvious extension of the technique described in ( , p.23], which comprises a second order and a fourth order equation describing the flow between two rotating, coaxial disks. The original problem definition
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