New Release of Numerical Library for C and C++
Numerical Algorithms Group (NAG), announces its new release of the globally renowned NAG C Library. Extensive new functionality added to the NAG C Library at the latest release provides programmers with over 1000 easily embedded numerical routines.
The new developments at Mark 8 make it far and away the largest commercially available numerical library for the C language. In addition to the considerable new functionality, Mark 8 will be available for 64-bit and 32-bit applications alike and feature compatibility with the latest compilers.
The flexible structure of the NAG C Library enables it to be called from many environments and packages such Microsoft .NET, Excel, MATLAB and various popular statistical packages making it ideal for a wide range of application environments.
With the increased strength in terms of size and functionality, the NAG C Library, Mark 8 will benefit anyone needing to add mathematical and statistical functionality to their applications. Of particular interest to those working within the finance industry will be the extended optimization chapter, which now incorporates enhanced sparse matrix techniques, critical for efficiently solving problems that involve a
very large proportion of zeros in the constraint or objective functions.
A typical example is in a portfolio optimization problem where a constraint exists on the percentage of the portfolio invested in stocks within a givenAdvertisement country. In such a problem there will be holdings specified for many stocks but most will be zero making the problem large but also predominantly sparse in nature.
Mark 8 will also provide a number of new modules and techniques in fields such as linear algebra and copulas. There is currently great interest in the mathematics of copulas from financial engineers and the modules for this branch of statistics within the new release will be a vital numerical tool for those wanting to use Gaussian or Student-t or other copula techniques to model multivariate statistical relationships
on computers. Copulas are also frequently applied to any form of stochastic simulation where a more flexible multivariate covariance structure is required.
The already extensive linear regression chapter in the NAG C Library has been further enhanced with the inclusion of routines for stepwise linear regression and mixed effects regression. Stepwise regression allows for the automatic selection of subsets of independent variates and is ideal for analyzing datasets with a large number of independent variates. The mixed effects regression routines allow the fitting models that contain both random and fixed variates; a type of modeling that is currently
used in a wide range of disciplines. In addition to the widespread enhancements to the statistical area of the NAG C Library the Time Series Analysis chapter has been enlarged with the addition of routines for the fitting of and prediction from a vector autoregressive moving average (VARMA) model.
NAG's C Library is available in a wide range of implementations, from PCs to supercomputers, covering Windows, Linux and major Unix platforms, ensuring that NAG's users are not constrained to a particular environment. In addition, users subscribing to NAG's Customer Support Service can have access via the Response Centre to the technical experts responsible for this software.
New at Mark 8 Summary:
- Constrained minimization for large sparse problems
- Constrained Quadratic Programming for large sparse problems
o Statistics: extended coverage including
- Copulas - Normal and Student's t
- Multivariate Normal, Student's t distribution random numbers
- Mixed effects regression
- Stepwise linear regression
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