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Extreme Optimization Numerical Libraries for .NET
Features
Extreme Optimization Numerical Libraries for .NET sets new standards
for usability and developer productivity
in numerical computing. It is the most intuitive numerical library for the .NET
framework. Its highly optimized classes for numerical computation cover a wide
range of applications. The classes are organized in
a consistent namespace and inheritance hierarchy.
The Extreme Optimization Numerical Libraries for .NET offer a true and
intuitive, object-centered approach to mathematical computing, without
compromising performance.
Extreme Optimization Numerical Libraries for .NET
includes classes for:
-
Complex numbers
- Curve fitting and interpolation: cubic splines, linear least squares, nonlinear least squares.
- Optimization in one or more dimensions.
- Solving equations in one or more variables.
- Numerical integration and differentiation: including robust adaptive integration.
- Special functions: Bessel and Airy functions, Gamma-related functions, exponential integrals.
Linear algebra (Details)
- Real and complex vectors and matrices.
- Vector types: General, band, constant, row and column vectors.
- Matrix types: General, triangular, symmetric, diagonal and band matrices.
- Matrix decompositions: LU, QR, Cholesky, Eigenvalue and Singular Value decompositions.
- Statistical Models: Simple, multiple and polynomial
regression. One and two-way ANOVA.
- Hypothesis Tests: 12 hypothesis tests, including the
z-test, t-test, F-test, and more advanced tests, such as the Anderson-Darling
test for normality, one and two-sample Kolmogorov-Smirnov test, and Levene's
test for homogeneity of variances.
- Statistical Distributions: 25 continuous and discrete
statistical distributions, including uniform, Poisson, normal, lognormal,
Weibull and Gumbel extreme value) distributions.
- Random numbers: Random variates from any distribution, 4
high-quality random number generators, low discrepancy sequences, shufflers.
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