General
- Machine floating-point constants.
- Common mathematical constants.
Complex numbers
- Double-precision complex number value type.
- Overloaded operators for all arithmetic operations.
- Extension of functions in System.Math to complex argument.
- Support for complex infinity and complex Not-a-Number (NaN).
Linear algebra
- Extensive vector and matrix classes.
- Special matrix types: triangular matrix, symmetrical matrix.
- Matrix factorizations: LU decomposition, QR decomposition, Cholesky decomposition.
- Solution of systems of simultaneous linear equations.
- Matrix inverse, determinant, condition number.
- Based on optimized LAPACK and BLAS routines.
- Real and complex versions of all classes. New!
Numerical integration and differentiation
- Numerical differentiation.
- Numerical integration using Simpson's rule and Romberg's method.
- Adaptive numerical integrator.
- Integration over infinite intervals.
- Optimizations for functions with singularities and/or discontinuities.
Curves
- Object-oriented approach to working with mathematical curves.
- Methods for: evaluation, derivative, definite integral, tangent, roots.
- Many basic types: constants, lines, quadratics, polynomials, cubic splines, Chebyshev approximations, linear combinations of arbitrary functions.
Curve Fitting and Interpolation
- Interpolation using polynomials, cubic splines, piewise constant and linear curves.
- Linear least squares fit using polynomials or arbitrary functions.
- Nonlinear least squares using predefined functions or your own.
- Predefined nonlinear curves: exponential, rational, Gaussian, Lorentz, 4PL, 5PL
- Weighted least squares
Solving equations
- Real and complex roots of polynomials.
- Roots of arbitrary functions: bisection.
- Systems of simultaneous linear equations.
- Systems of nonlinear equations.
Special functions
- Over 40 special functions not included in the standard .NET Framework class library.
- Greatest common divisor, least common multiple, decomposition into prime factors.
- Gamma and related functions
- Ordinary and Modified Bessel functions of the first and second kind.
- Airy functions and their derivatives.
- Exponential integral, sine and cosine integral, logarithmic integral.
Descriptive Statistics
- Measures of central tendency: mean, median, trimmed mean, harmonic mean, geometric mean.
- Measures of scale: variance, standard deviation, range, interquartile range, absolute deviation from mean and median.
- Higher moments: skewness, kurtosis.
Probability Distributions
- Probability density function (PDF).
- Cumulative distribution function (CDF).
- Percentile or inverse cumulative distribution function.
- Moments: mean, variance, skewness and kurtosis.
- Generate random samples from any distribution.
- Parameter estimation for selected distributions New!
Continuous Probability Distributions
- Beta distribution.
- Cauchy distribution.
- Chi-squared distribution.
- Erlang distribution.
- Exponential distribution.
- F distribution.
- Gamma distribution.
- Gumbel distribution.
- Laplace distribution.
- Logistic distribution.
- Lognormal distribution.
- Normal distribution.
- Pareto distribution.
- Rayleigh distribution.
- Student t distribution.
- Triangular distribution.
- Uniform distribution.
- Weibull distribution.
Discrete Probability Distributions
- Bernoulli distribution.
- Binomial distribution.
- Geometric distribution.
- Hypergeometric distribution.
- Negative binomial distribution.
- Poisson distribution.
- Uniform distribution.
Histograms
- One-dimensional histograms.
- Probability distribution associated with a histogram.
Analysis of variance (ANOVA)
- One and two-way ANOVA.
- One-way ANOVA with repeated measures.
Regression analysis
- Simple, multiple, and polynomial regression
- Nonlinear regression
- Logistic regression New!
- Confidence intervals for regression parameters.
Time series analysis
- Treat several observation variables as a unit
- Change frequency of time series
- Automatically apply predefined aggregators
- Over 30 transformations of Time Series Data
Statistical tests
- One and 2 sample z-test, one and 2 sample t-test.
- F-test, chi-square test
- Goodness-of-fit tests
- Bartlett and Levene tests for homogeneity of variances.
- McNemar and Stuart-Maxwell test. New!
Random number generation
- Compatible with the .NET Framework's System.Random.
- Four generators, with varying quality, period and speed to suit your application.
- Generate random samples from any distribution.
- Faure and Halton sequences
- Shufflers and randomized enumerators
System Requirements
.NET Framework 1.1, 2.0, 3.0 or 3.5.
Technical Information
Component Type - Contains the following types of components...
