.NET / C# Numerical Library

Advanced numerical analysis

Simplify complex code by using a 100% native C# library. The IMSL Library for C# can be referenced from any .NET framework language including C#, F#, and Visual Basic .NET.

Version 6.5.2 of the IMSL Library for C# provides embeddable native C# analytics that includes mathematical, statistical, data mining and financial algorithms for the .NET framework.

“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

Since .NET framework 4.0, Microsoft has extended the threading capabilities of the .NET framework with the Task Parallel Library. The IMSL Library for C# has integrated these threading patterns into dozens of functions, resulting in easy access to parallel-processing performance increases that take advantage of multicore hardware.

Embed analytics in your C# application or SQL Server database

The algorithms available within the IMSL Library for C# 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. It is also effective for ASP.NET as well as ADO.NET implementations.


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.