100+ New Algorithms for C and C++ Programmers in the NAG C Library, Mark 24

New techniques include: Confluent & Gauss Hypergeometric Functions, Volatility, Quadratic Eigenvalue Problems, Matrix Functions, plus a host of new Optimization routines

4 June 2014 - The Numerical Algorithms Group (NAG) announces new functionality added to its numerical library for C and C++ programmers. The new functionality included at Mark 24 of the NAG C Library brings the number of available functions to over 1,500, all of which are expertly documented and includes extensions in the areas of optimization, wavelet transforms, time series analysis, random number generators, correlation and regression analysis, statistics and hypergeometric functions.

  • Hypergeometric function (1F1 and 2F1)
  • Nearest Correlation Matrix
    • Elementwise weighted nearest correlation matrix
  • Wavelet Transforms & FFTs
    • Three-dimensional discrete single level and multi-level wavelet transforms
    • Fast Fourier Transforms (FFTs) for two-dimensional and three-dimensional real data
  • Matrix Functions
    • Matrix square roots and general powers
    • Matrix exponentials (Schur-Parlett)
    • Fréchet Derivative
    • Calculation of condition numbers
  • Interpolation
    • Interpolation for 5D and higher dimensions
  • Optimization
    • Local optimization: Non-negative least squares
    • Global optimization: Multi-start versions of general nonlinear programming and least squares routines
    • RNG's
    • Brownian bridge and random fields
  • Statistics
    • Gaussian mixture model
    • Best subsets of given size (branch and bound)
    • Vectorized probabilities and probability density functions of distributions
    • Inhomogeneous time series analysis, moving averages
    • Routines that combine two sums of squares matrices to allow large datasets to be summarised
  • Data fitting
    • Fit of two-dimensional scattered data by two-stage approximation (suitable for large datasets)
  • Quadrature
    • One-dimensional adaptive for badly-behaved integrals
  • Sparse eigenproblem
    • Driver for real general matrix, driver for banded complex eigenproblem
    • Real and complex quadratic eigenvalue problems
  • Sparse linear systems
    • block diagonal pre-conditioners and solvers
  • ODE solvers
    • Threadsafe initial value ODE solvers
  • Volatility
    • Heston model with term structure

The new NAG C Library contains additional functions that have been added in response to customer requests, and further enhancements contributed by NAG's expert developers and collaborators.

The inherent flexibility of the mathematical and statistical functions in the NAG C Library enable it to be used across multiple programming languages, environments and operating systems including Excel, Java, Microsoft .NET, Python, Visual Basic and many more.

Speaking of Mark 24, a Senior Developer at one of NAG's partners said "I was particularly pleased to see the addition of the Log Matrix and Exponential Matrix functions and the fact that these solvers worked with general matrices as well as symmetric is particularly useful for me. The further additions to the suite of Nearest Correlation Matrix functions as well as new additions to the Eigenvalues Chapter are of course very valuable too. I am also interested to experiment with the Real Confluent Hypergeometric function as this may have several uses in future projects"

More benefits of the NAG C Library:

  • Highly detailed documentation giving background information and function specification. In addition it guides users, via decision trees, to the right function to solve their problem.
  • Expert Support Service direct from NAG's algorithm development team - if users need help, NAG's development team are on hand to offer assistance.
  • Example programs are included in the Library to help users get started with its functions. If a specific example program requires any input data a helpful expected results file is available.

For more information visit the website or contact us at nagmarketing@nag.co.uk.