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NAG Library adds New Algorithms for Application Developers

nag_logoToday the Numerical Algorithms Group (NAG) released their latest NAG Library including over 80 new mathematical and statistical algorithms. Now available with over 1,800 functions, version 25 includes extensions in the areas of Change Point Analysis, LARS / Lasso / Forward Stagewise Regression, Mixed Integer Nonlinear Programming, Nearest Correlation Matrix, Unscented Kalman Filter, plus a new OpenMP Utilities chapter.

I am delighted to see the new content addressing customer demand,” John Holden, NAG’s VP Global Markets commenting on the new release. “It is particularly pleasing to see the content being implemented in collaboration with our customers and academic partners. NAG continues to collaborate with leading scientists from around the world. With Mark 25 we welcome to the NAG family Prof Klaus Schittkowski, University of Bayreuth and Dr Rebecca Killick, Lancaster University.”

New NAG Library mathematical and statistical content includes:

  • Many new Matrix Functions
  • Least Angle Regression (LARS), Least Absolute Shrinkage and Selection Operator (LASSO) &Forward Stagewise Regression
  • Nearest Correlation Matrix updates
  • Unscented Kalman Filter
  • Change Point Analysis
  • High Dimensional Quadrature using Sparse Grids
  • Bandwidth Reduction of Sparse Matrix by Reverse Cuthill-McKee Reordering
  • Solutions to the classical Travelling Salesman Problem
  • OpenMP Utilities

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

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