09-21-2010, 02:07 PM

IMSL Numerical Libraries

The IMSL Numerical Libraries have been the cornerstone of high-performance and desktop computing applications in science, technical and business environments for well over three decades. These embeddable mathematical and statistical algorithms are used in a broad range of applications -- including programs that help airplanes fly, predict the weather, enable innovative study of the human genome, predict stock market behavior and provide risk management and portfolio optimization. The algorithms embody the combination of High Performance Computing and High Productivity Computing. Significant benefits can be realized with the product’s ability to accelerate development time, reduce coding hassle, improve quality, and reduce development costs.

Embeddable Mathematical and Statistical Functionality

The IMSL Libraries are a comprehensive set of mathematical and statistical functions that programmers can embed into their software applications. The libraries save development time by providing pre-written mathematical and statistical algorithms that can be embedded into C, C# for .NET, Java™ and Fortran applications, enhancing return on investment and programmer productivity. The IMSL Libraries can also be used from Python using PyIMSL Studio or the PyIMSL wrappers. Beyond choice of programming language, the IMSL Libraries are supported across a wide range of hardware and operating system environments including Windows, Linux, Apple and many UNIX platforms.

The IMSL Libraries and support services emphasize user productivity and cost-effectiveness providing a significant return on investment by saving up to 95% of the time and cost of developing numerical algorithms.

Mathematics:

- Matrix Operations

- Linear Algebra

- Eigensystems

- Interpolation & Approximation

- Numerical Quadrature

- Differential Equations

- Nonlinear Equations

- Optimization

- Special Functions

- Finance & Bond Calculations

- Genetic Algorithm

Statistics:

- Basic Statistics

- Time Series & Forecasting

- Nonparametric Tests

- Correlation & Covariance

- Data Mining

- Regression

- Analysis of Variance

- Transforms

- Goodness of Fit

- Distribution Functions

- Random Number Generation

- Neural Networks

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* Intel.Fortran IA32

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* Intel.Fortran EM64T

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* C# NET

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