Least squares: a case study in optimization

The F#.NET Journal just published an article about curve fitting:

"The challenge of finding the least squares best fit of a linear sum of functions is a common problem in regression. Linear algebra provides a powerful and general solution by expressing this problem in terms of matrices and then computing the QR decomposition in order to solve the matrix equation. This article describes a remarkably simple implementation of QR decomposition in F# before developing progressively more optimized implementations using the guidance of performance profiles and without sacrificing generality. In particular, heavy use of the F# keyword "inline" is made in order to express efficient reusable numerical methods..."

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