Numerical Analysis Using R
Solutions to ODEs and PDEs

Practical numerical methods for solving differential equations are illustrated in the increasingly popular open source language R.

Graham W. Griffiths (Author)

9781107115613, Cambridge University Press

Hardback, published 26 April 2016

632 pages, 182 b/w illus. 15 colour illus.
26 x 18.3 x 3.7 cm, 1.32 kg

'Numerical Analysis Using R is a very interesting text on the theory and practical implementation of numerical methods for approximating solutions to differential equations. The book contains a wealth of information presented in such a way as to be accessible to a wide audience of engineers, mathematicians and other scientists. This book manages to be a unique contribution to the collection of numerical methods texts …' Jason M. Graham, MAA Reviews

This book presents the latest numerical solutions to initial value problems and boundary value problems described by ODEs and PDEs. The author offers practical methods that can be adapted to solve wide ranges of problems and illustrates them in the increasingly popular open source computer language R, allowing integration with more statistically based methods. The book begins with standard techniques, followed by an overview of 'high resolution' flux limiters and WENO to solve problems with solutions exhibiting high gradient phenomena. Meshless methods using radial basis functions are then discussed in the context of scattered data interpolation and the solution of PDEs on irregular grids. Three detailed case studies demonstrate how numerical methods can be used to tackle very different complex problems. With its focus on practical solutions to real-world problems, this book will be useful to students and practitioners in all areas of science and engineering, especially those using R.

1. ODE integration methods
2. Stability analysis of ODE integrators
3. Numerical solution of PDEs
4. PDE stability analysis
5. Dissipation and dispersion
6. High resolution schemes
7. Meshless methods
8. Conservation laws
9. Case study: analysis of golf ball flight
10. Case study: Taylor–Sedov blast wave
11. Case study: the carbon cycle.

Subject Areas: Statistical physics [PHS], Probability & statistics [PBT], Numerical analysis [PBKS]