An open-source project

The reliability of the algorithms provided by the library is emphasized by the complete availability of the sources, which are released under the GNU Lesser General Public License (LGPL) Version 3.

Full usability from the most popular computing environments

The library can be directly used within the most popular computing environments, such as MATLAB, GNU Octave, Mathematica, and R.



The zip archive collecting the compiled version of the library and the documentation (both Javadoc and the user guide) can be downloaded here:

MD5 checksum: de47e99943b6ccaaf2fc9561235971c1


The first section of the user guide explains in detail how to link the library to your Java application or how to use it within the supported computing environments. Impatients java programmers can develop their own first application very easily by adding to the java classpath the path of the jar archive MpTheory-1.0.jar. Please remember that the lib folder, which contains the jar archives of the imported libraries, has to be stored in the same location of the jar archive of the library.


Complete sources are available here as a NetBeans IDE 7.3 project:

MD5 checksum: d0a9cf925eedeb72df28972e65aaa1bb


As it is possible to see in the Javadoc documentation, the library is organized in three Java packages:

  1. the package modeling comprising all the Java classes that are useful for creating MP models;
  2. the package simulation comprising a set of algorithms for simulating MP models;
  3. the package regression comprising a set of algorithms for inferring MP models starting from time series of observations.

We refer to the documentation for details.

Sources of the JEP project imported in the library

The Jep project provides an open-source java library for parsing and evaluating mathematical expressions. The library has been a little modified in order to support delays, as it is explained in the user guide. The sources of the modified version of the library can be downloaded here as a NetBeans IDE 7.3 project:

MD5 checksum: f195dd9609fd1446b77d7728920f65e8


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