Fortran Numerical Library
Embeddable numerical analysis functions for Fortran applications
The IMSL Fortran Numerical Library is the standard for high performance computing commercial mathematics and statistics libraries, providing:
Learn what's new with in the latest release or see a full features list here.
University of Wisconsin
The gold standard for over four decades
With over 1000 fully supported algorithms, the IMSL Fortran Numerical Library is the most comprehensive mathematics and statistics library available. Highly robust and reliable, it contains proven technology that has been thoroughly tested, well documented, continuously maintained, optimized on various platforms and used by developers worldwide for four decades. Instead of writing, testing and documenting complex mathematical and statistical algorithms from scratch or getting them from open source, developers use the algorithms provided in the IMSL Fortran Numerical Library to help accelerate application development and time to market.
The original, easy-to-use Fortran Library
The IMSL Fortran Numerical Library is the most convenient to use Fortran library available today. Features that make your developers more productive include:
| 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 |