Announcing Computational Methods for Numerical Analysis

For about two years, I’ve been working on a book called Computational Methods for Numerical Analysis with R (CMNA), which will present an outline of numerical analysis topics with original (and simplified) implementations in R at a level appropriate for a graduate student or advanced undergraduate. Last night, I sent the latest draft to my editors, and I am quite pleased to say it should be heading into production, soon.

The organizational structure of the text is based roughly on the organizational structure of MAPL 460 15-20 years ago:

1. Introduction to Numerical Analysis
2. Error Analysis
3. Linear Equations
4. Interpolation and Extrapolation
5. Numerical Integration
6. Root Finding and Optimization
7. Differential Equations

I’ve wanted to write this book for a long time and I am happy to say it will be published by CRC Press in 2017 as part of their Numerical Analysis and Scientific Computing Series. A lot of numerical analysis is taught using MATLAB. I have a lot of respect for MATLAB having used it for 15 years. But there’s room for other options. Fortran and C are not viable today, but R is readily available for free. And a lot of students are already picking it up for statistics classes.

There are two other books, that I know of, that provide numerical analysis in R. Both are aimed at providing guidance on using the existing implementations within R, also published by CRC Press:

• Using R for Numerical Analysis in Science and Engineering, by Victor A. Bloomfield
• Introduction to Scientific Programming and Simulation Using R, Second Edition, by Owen Jones, Robert Maillardet, and Andrew Robinson

Both are excellent texts, but my book is different in that it will provide the underlying algorithms and a variety of them for most problems. I will be posting additional details as they become available.

Image by Skitterphoto / Pixabay.