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Major Update To NAG Library For C and C++

The Numerical Algorithms Group (NAG) has new functionality added to its numerical library for C and C++ programmers.

NOTE: Although named a "group", NAG is a commercial software company dedicated to providing mathematical and statistical solutions very often for High-Performance Computing (HPC) environments.

The new functionality can be found at Mark 23 of the NAG C Library. It brings the number of routines to 1452 and includes "entirely new" chapters plus extensions in the areas of statistics, nonlinear equations, wavelet transforms, ordinary differential equations, interpolation, surface fitting, optimization, matrix operations, linear algebra, large scale linear systems, and special functions.

NAG sells its concepts on the precepts of a simple equation. Software developers writing in C / C++ require accurate numerical functionality and so could write their own numerical code, but this can be extremely time consuming (especially for any nontrivial component).

So then, if freeware is too risky an option, NAG offers what it insists is a "trusted numerical function" that has been acutely tested and well documented. Plus of course, the routines in the NAG C Library enable it to be used across multiple programming languages, environments, and operating systems including Excel, Java, Microsoft .NET, Visual Basic, etc.

An anonymous quantitative analyst at an investment bank is on the record as saying that he was most excited about the inclusion of matrix functions (especially exponential), the additional nearest correlation matrix functions, the skip ahead for Mersenne Twister (as this is pretty non-trivial to implement), and the vectorized simple functions in the Statistics and Special Functions chapters.

NOTE: The Mersenne twister is a pseudorandom number generator based on a matrix linear recurrence over a finite binary field. It provides for fast generation of very high-quality pseudorandom numbers, having been designed specifically to rectify many of the flaws found in older algorithms.

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