Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use.
Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.
Country of Publication:
30 September 2020
Preface Introduction to Numerical Analysis Error Analysis Linear Algebra Interpolation and Extrapolation Differentiation and Integration Root Finding and Optimization Differential Equations Suggested Reading Index
Reviews for Computational Methods for Numerical Analysis with R
The author says that the book is written for advanced undergraduate or first year graduate student as a collateral text for numerical analysis courses. The theoretical part of numerical analysis is mostly omitted, the focus is to present a working R code for many basic tasks of numerical computation including linear algebra, interpolation, numerical integration, root finding and optimisation and differential equations. The presentation is very clear and reader friendly. -Matti Vuorinen (Turku), in Zentralblatt Mathematik, April 2018