.NET / C# Numerical Library

Advanced numerical analysis

As the only numerical library of its kind to offer unprecedented analytic capabilities and charting, the IMSL .NET Numerical Library can be referenced from any .NET framework language including C#, F#, and Visual Basic .NET. Version 6.5 of the IMSL .NET Libraries provides the most comprehensive, high-performing, and accessible mathematical, statistical, and financial algorithms for the .NET framework and Microsoft Silverlight.

“The IMSL C# Library enables us to quickly and efficiently provide advanced data analysis capabilities to Six Sigma professionals within our SigmaWorks Professional and RiskWizard Software solutions ... We were impressed with how easy it is to call IMSL C# Library objects from visual Studio.”
Scott Patrias,
Next Sigma, Inc
software development manager

Achieve performance increases with new parallel computing capabilities

With .NET framework 4 and Visual Studio™ 2010, Microsoft has extended the threading capabilities of the .NET framework with the Task Parallel Library. The IMSL .NET Library has integrated these threading patterns into dozens of functions, resulting in easy access to parallel-processing performance increases that take advantage of multicore hardware.

Save development effort by embedding IMSL .NET functions

The algorithms available within the IMSL .NET Library cover all of the major categories of functionality commonly used in numerical analysis, from commonly used math and statistical analysis functions like optimization and regression to advanced neural network and classification technology. This math and statistical algorithm functionality can be applied to an unlimited set of applications, such as bioinformatics and life sciences, fraud detection, risk management and portfolio optimization, manufacturing yield analysis, and more.


Functional areas included in the IMSL .NET Library:

Mathematical Statistical Charting Data mining
Linear Systems Basic and Nonparametric Statistics Function and Spline Neural Network Engines
Eigensystem Analysis Time Series and Forecasting Line, Pie, Scatter, Bar, and Box Neural Network Data Pre-processors
Interpolation and Approximation Tests of Goodness of Fit Polar, Area, Contour, and Histogram Naïve Bayes Classification
Nonlinear Equations Regression Date and Time Support
Optimization Multivariate Analysis Fully Interactive Capabilities
Finance and Bond Calculations Probability Distribution Functions High-Low-Close
Differential Equations Random Number Generator Heat Map and Tree Map
And many more...

Learn more about our capabilities.