Projects / Meta.Numerics

Meta.Numerics

Meta.Numerics is a Mono-compatible .NET library for scientific and numerical programming. It includes functionality for matrix algebra (including SVD, non-symmetric eigensystems, and sparse matrices), special functions of real and complex numbers (including Bessel functions and the complex error function), statistics and data analysis (including PCA, logistic and nonlinear regression, statistical tests, and nonuniform random deviates), and signal processing (including arbitrary-length FFTs).

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Recent releases

  •  20 Aug 2013 17:27

    Release Notes: This release adds multidimensional numerical integration, polynomial interpolation and arithmetic, exact null distributions for small samples, and other improvements.

    •  10 Sep 2012 18:30

      Release Notes: This release adds faster FFT, more advanced functions, multivariate root-finding, iterative solutions of large, sparse matrix systems, and more fits.

      •  12 Apr 2011 16:36

        Release Notes: A major release with a lot of new functionality: SVD, sparse matrices, FFTs, PCA, logistic regression, Kruskal-Wallis test, loading data from DB or Excel, more probability distributions, and various performance improvements.

        •  05 Oct 2010 15:48

          Release Notes: Notable new features in this release include: more special functions (associated Legendre and Laguerre polynomials, elliptic integrals, and integer partitions), faster matrix operations (multiplication, inversion, and LU and QR decomposition), more statistical tests (Z test, sign test, and one-way ANOVA), more probability distributions (including discrete distributions like Binomial and Poisson), and bugfixes and improved documentation.

          •  10 May 2010 18:27

            Release Notes: Many new special functions including 6j functions, modified Bessel functions, Airy functions, Coulomb wave functions (accurate even in the quantum tunneling region), and the dilogarithm function (for real and complex values). Multivariate linear regression with covariances and F-test for goodness of fit. Improved documentation.

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