By Chambers, John M
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1. COMPUTATIONAL METHODS ✐ 25 of time series, including the fast Fourier transform; numerical integration. Linear models: A major advance in this period came from numerical techniques based on matrix decompositions. Previously, old hand-calculation techniques (solving “normal equations”) had been used. The basic linear model functions in R still use revised versions of the QR and other decompositions from this period. Singular-value and eigenvalue algorithms were also important for statistical applications.
Book” — 2016/4/28 — 14:19 ✐ 32 ✐ CHAPTER 2. 3 Functional, Object-Based S Once a decision had been made to create the “New S”, the implementation proceeded fairly rapidly, in effect merging work on QPE and on modernizing S. By 1988, the new S was being distributed and described in The New S Language , which became known as “the blue book” from the color of its cover. This was Version 3 of S, or S3 for short. It was not back-compatible with previous versions. This was the only time (so far) that a version of either S or R has been fundamentally incompatible in the sense that the majority of the programming done for the previous version would not work with the new version.
However, the interface language had important advantages, worth considering today in dealing with challenging computations where efficiency matters. 1. Because the interface language did end up as Fortran, it could produce computationally efficient code with direct access to much existing software for serious numerical methods. 2. At the same time, having a customized language allowed the programming to look more like S (and with less primitive tools, one could have gone much farther in this direction).
Extending R by Chambers, John M