IMSL Numerical Libraries

Battle-tested algorithms from prototype to production

Analyzing data has never been more important — or harder. Getting actionable information from your large and disparate datasets can often determine if your organization meets its goals. Create competitive differentiation and unlock innovation by using the most trusted, tested, and reliable algorithms available. Backed by a team of mathematicians and statisticians, IMSL® Numerical Libraries allow you to address complex problems quickly with a variety of readily-available algorithms. With IMSL you get consistency from prototype to production.

The largest collection of commercially-available mathematical and statistical functions for data mining and analysis, IMSL embeddable algorithms are used in a broad range of applications across all industries. Organizations in finance, telecommunications, oil and gas, government, aerospace, and manufacturing depend on the robust and portable IMSL Libraries to efficiently build high-performance, mission-critical applications, including applications used to enable the innovative study of the human genome. Create, innovate, and implement technology to meet your strategic objectives.

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Embeddable mathematical and statistical functionality

IMSL Libraries save development time by providing optimized mathematical and statistical algorithms that can be embedded into C, C++, .NET, Java™, and Fortran applications, including many databases. IMSL enhances application performance, reliability, portability, scalability, and maintainability as well as developer productivity. IMSL Libraries are supported across a wide range of languages as well as hardware and operating system environments including Windows, Linux, Apple, and many UNIX platforms.

“IMSL Numerical Libraries offer the most comprehensive, tested statistical functionality available, support major computing platforms, and were easily embeddable into the GlyphWorks solution.”
Jon Aldred,
HBM-nCode
Product Manager

Functional areas in the IMSL Numerical Libraries:

Data mining and forecasting functionality Statistical functionality Mathmatical functionality
Regression Time series and forecasting Optimization
Cluster analysis Nonparametric tests Matrix operations
Auto_ARIMA Analysis of variance Linear algebra
ARCH, GARCH Generalized linear models Eigensystem analysis
Principal components analysis Goodness of fit Interpolation and approximation
Factor analysis Distribution functions Quadrature
Discriminant analysis Random number generation Differential equations
Generalized categorical models Hypothesis testing PDEs
Bayesian seasonal model Design of experiments Feynman-Kac solver
Statistical process control Transforms
Multivariate analysis Nonlinear equations
Correlations and covariance Linear and nonlinear programming
Multidimensional scaling Special functions
Summary statistics Utilities

Case study - Risk-AI

“For anything analytical, IMSL is the default — we haven’t found anything better” – see how Risk-AI avoided reinventing algorithm development.

Case study - University of Wisconsin

Dr. Lentz decided to transition some of his economics projects and applications from high-level MATLAB and Gauss programming environments to Fortran. Learn how IMSL provided a smooth transition.