UPDATE:The latest version of the NAG Fortran Library now includes over 250 new routines, taking the total number of user-callable routines in Mark 21 to over 1450. As the world’s leading provider of mathematical and statistical algorithms, NAG can boast the largest collection of quality numerical algorithms available today. Unrivaled functionality from the routines in the globally renowned NAG Fortran Library embraces the world’s most widely used mathematical and statistical algorithms. Additions to the NAG Fortran Library include new optimization routines offering real performance gains over previous routines. Comparative tests have shown marked improvements in speed of computation. An essential tool for personnel with an interest in computing portfolios or in tracking indices, this release will be of particular benefit to analysts and quants in the financial industry. Also of particular benefit to the finance industry are new and improved random number generation routines, (which are heavily used when carrying out stochastic simulation), the inclusion of copulas, and improvements to the quasi-random number interfaces. A key component is the inclusion of a new chapter of routines for large scale eigenvalue problems. Eigenvalue and eigenvector problems are ubiquitous. Typically, for example, engineers perform such calculations to complete a vibration analysis on a structure. The early problems of the Millennium Bridge across the Thames were a fine demonstration of what can go wrong. The new suite of routines is capable of solving very large systems, and can handle both standard and generalized eigenproblems. NAG is proud to have provided two of the major contributors to the LAPACK project. Jeremy du Croz has since retired, but NAG Principal Technical Consultant, Sven Hammarling, is still active in this area. Under his guidance, NAG has completed the task of putting the whole of LAPACK 3 into the library software. Because Hammarling is still actively involved in the project, NAG is able to ensure that only the latest code is included, complete with error corrections. Expansions in linear regression software included in the latest release will benefit a wide range of industries and academic areas. A stepwise regression routine allows the user to examine a large number of models in a short period of time and is an excellent tool for hypothesis generation. When dealing with databases having a large number of potentially interesting explanatory variables, stepwise regression can be used to quickly select the most interesting subset of variables, which can then be examined in more detail using other techniques. The statistical area of mixed effects regression, also included in the new release, can be applied in a wide range of different situations and as such is becoming common in a wide range of fields including the pharmaceutical and engineering sectors. Mark 21 of the NAG Fortran Library continues to provide a high degree of flexibility so that components can be easily used on their own or incorporated into other packages. Software partners including PeopleSoft and Maplesoft embed NAG functionality into their own packages to take advantages of the quality, reduction in maintenance and short time to market afforded by NAG algorithms. Covering Windows, Linux and major UNIX platforms, the NAG Fortran Library is available on machines ranging from PCs to supercomputers. Not restricted to a single environment, NAG customers can also benefit from the Library’s design that allows algorithms to be called from other languages such as Microsoft Visual C++, Visual Basic, Excel and Java. Technical help for anyone subscribing to NAG’s Customer Support Service is available from the experts responsible for the relevant software. Commenting on the new release, Rob Meyer, CEO, NAG Group, said: “With this latest release of the NAG Fortran Library, we are able to offer our customers the largest collection of quality numerical algorithms currently available. By using the NAG Fortran Library, software developers will not only reduce the time spent in producing individual routines, but will have the reassurance of a tried and tested algorithm that is fully compatible with their own program.”