Java™ Numerical Library

Advanced numerical analysis and charting for Java

The JMSL Numerical Library is the broadest collection of mathematical, statistical, financial, data mining, and charting classes available in 100 percent Java. It is the only Java programming solution that combines integrated charting with the reliable mathematical and statistical functionality of the industry-leading IMSL Library algorithms. This blend of advanced numerical analysis and visualization on the Java platform allows organizations to gain insight into valuable data and share analysis results across the enterprise quickly.

Mathematical, statistical, and charting functionality in JMSL
“The flexibility provided by the IMSL Library has permitted us to build a unique and flexible post-processing system, allowing us to compete head-to-head in the global weather services market”
Brian Peters,
Senior Development Meteorologist

The JMSL Library provides robust data analysis and visualization technology for the Java platform and a fast, scalable framework for tailored analytical applications. By leveraging its pre-built algorithms, users can save weeks or months of development effort by embedding JMSL Library functions rather than building new algorithms from scratch. The intuitive object-oriented programming interface allows Java developers to be immediately productive.

The JMSL Library provides a broad range of functionality, from basic algorithms such as linear algebra and regression to advanced neural network forecasting and other data mining, modeling, and prediction technologies. The neural network forecasting classes have tremendous potential for businesses by offering the ability to build predictive models using historical data and training the network to optimize the model over time as more information is obtained. This 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.

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...

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