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This information is from the company website (URL: bit.ly/iQlVrx).

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 CC# for .NETJava™ and Fortranapplications, 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 asignificant return on investment by saving up to 95% of the time and cost of developing numerical algorithms.

Functional areas included in the IMSL C# Numerical Library:
Mathematics Statistics
  • Matrix Operations
  • Linear Algebra
  • Eigensystems
  • Interpolation & Approximation
  • Numerical Quadrature
  • Differential Equations
  • Nonlinear Equations
  • Optimization
  • Special Functions
  • Finance & Bond Calculations
  • Genetic Algorithm
  • 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

Benefits of Embedding the IMSL® Libraries in Your Analytic Applications

Accelerate Development
  • Analytical building blocks eliminating the need to write code from scratch
  • Numerical algorithms are developed, tested, documented, and ready to go
  • Save up to 95% of the time required to research and develop algorithms
  • Consistent commercial quality interfaces improve developer productivity
Develop Better Software Applications
  • You don't have to worry about coding and testing the numerical algorithms
  • Free up your developers' bandwidth for critical application-specific feature development
Develop Flexible Software Applications
  • The IMSL Libraries are written in the standard languages of C, C#, Java, and Fortran
  • Embed numerical analysis algorithms seamlessly into existing solutions
  • Applications built in C++, Python or any .NET language can easily reference the IMSL Libraries
Improve Quality and Reduce Uncertainty
  • The IMSL Libraries simplify your projects
  • A simpler project means a more predictable development and QA schedule
  • All IMSL algorithms are fully tested and qualified against proven testing criteria
  • QA efforts can focus on core application testing, not algorithm testing
  • The IMSL Libraries are fully documented and supported
Reduce Costs
  • The IMSL Libraries save up to 95% of algorithm development costs
  • The IMSL Libraries eliminate many hidden costs associated with algorithm development and support:
    • Background research
    • Debugging and QA
    • Porting to your specific environment
    • Documentation
    • Maintenance
    • Scaling for larger deployments
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IMSL® Library Return on Investment (ROI)


Numerical Analysis Algorithm Development: More costly than you may think 

 

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