NAG announces the launch of the new NAG Toolbox for MATLAB

New NAG toolbox for MATLAB gives users access to extensive new numerical functionality

April 2008. The Numerical Algorithms Group (NAG), provider of world class mathematical and statistical components, is delighted to announce the availability of the NAG Toolbox for MATLAB. The NAG Toolbox for MATLAB allows users to call NAG’s highly regarded numerical routines directly, using customized interfaces, from within the MATLAB environment. The Toolbox gives access to increased mathematical and statistical functionality, which was previously unavailable or accessible only by purchasing multiple toolboxes.

The NAG Library, which is accessed via the NAG Toolbox for MATLAB, is the largest and comprehensive collection of mathematical and statistical algorithms available today. It is used by many of the worlds most prominent finance houses and institutions, by academics in R&D and education and many other industries because of its reputation for quality, flexibility and robustness.

MATLAB users benefit from using the NAG Toolbox for MATLAB by:

Increased productivity - NAG routines have been written by experts and are globally renowned for their quality, flexibility and robustness
ALL NAG routines are accompanied by expert and unique documentation making the selection of the right algorithm quick and easy
Also included in the documentation for each NAG Library routine is example MATLAB code showing how to call the routine
Numerical code is easier to read and maintain as many routine arguments become optional or unnecessary

One of the key benefits of the NAG Toolbox for MATLAB is the extensive integrated documentation that accompanies the product. Included in this are descriptions of every routine, its purpose and an example of use, which helps users pick the right routine for their problem. This comprehensive documentation, for which NAG is renowned the world over, is not currently available using MATLAB independently, or in combination with other specialist toolboxes.

Results from an extensive beta test of the product have been very positive. A tester from the Banco de Portugal said of the product “The NAG Toolbox for MATLAB proved to be very fast and precise both in the solution of the system of nonlinear equations and the Inverse Laplace transform. It proved much more reliable than other methods we had tested”. A Research Fellow and Doctoral Candidate in Mathematical Finance also tested the toolbox and commented “I am impressed by the optimization algorithms provided by the NAG Toolbox for MATLAB. It improves the results for my maximum likelihood estimations for situations. Ordinary algorithms perform poorly in these situations.”

Speaking about the NAG Toolbox for MATLAB, NAG Chief Technical Officer Mike Dewar said “We know that an increasing number of people don't want to program in traditional programming languages like Fortran or C. By making our algorithms available to MATLAB users via the NAG Toolbox for MATLAB we can bring the extensive benefits of the NAG Library to a new generation of engineers and scientists".

Product Availability and Compatibility Information

The NAG Toolbox for MATLAB at its launch is available for Microsoft Windows 32 bit and Linux 32 and 64 bit and is compatible with MATLAB versions 2007a, 2007b, and 2008b. A current NAG Fortran Library licence is required to enable the use of the Toolbox. For more information contact sales@nag.co.uk.

Contact details:

Katie O’Hare

Marketing Communications Manager

NAG Ltd

Email: katie.o’hare@nag.co.uk

Web: http://www.nag.co.uk

About NAG

The Numerical Algorithms Group (NAG) is dedicated to making world-class cross-platform mathematical, statistical, data mining components and tools for developers as well as 3D visualization application development environments. NAG serves it customers from offices in Oxford, Chicago and Tokyo supporting over 10,000 customer sites worldwide in finance, engineering, and scientific research. NAG software is the choice of over 25 independent software vendors including Oracle, IBM, DemandTec and many others.