Numerical Analysis for Statisticians


Numerical Analysis for Statisticians by Kenneth Lange 2010
Although this book doesn’t have any code in in it, it is still useful. The theory and equations are well defined and easy enough to read.
I went to a talk on FFT and Python at OSCON 2013. Sound Analysis with the Fourier Transform and Python, given by Caleb Madrigal.
Chapter 19 on Fourier Transforms goes along nicely with the talk. Caleb presented the formulas and talked about which ones to use. This book gives you all the details you need for choosing formulas and libraries when implementing Fourier Transforms.

A Short History of Random Numbers, and Why You Need to Care given by Matthew Garrett, was another talk that I went to. Chapter 22 Generating Random Deviates is a nice over view of some of the material covered in the talk.

In general this is a good book, I just wish that it had some code examples, pseudo code, algorithms etc. It is not easy to take equations and turn them into code.