To get you started right away with creating your own statistical applications using the Extreme Optimization Numerical Libraries for .NET, we are providing these QuickStart Samples. See our Sample Applications page for some real-life applications.
Illustrates how to create and manipulate data frames using classes in the Extreme.DataAnalysis namespace.
Indexes and Labels
Illustrates how to use indexes to label the rows and columns of a data frame or matrix, or the elements of a vector.
Illustrates how to perform basic data wrangling or data munging operations on data frames using classes in the Extreme.DataAnalysis namespace.
Illustrates how to transform and manipulate the columns of a data frame.
Sorting and Filtering
Illustrates how to sort and filter data used for data analysis.
Grouping and Aggregation
Illustrates how to group data and how to compute aggregates over groups and entire datasets..
Illustrates how to create histograms using the Histogram class in the Extreme.DataAnalysis namespace.
Illustrates how to work with complex numbers using the DoubleComplex structure.
Illustrates how to use additional elementary functions.
Illustrates the basic use of the arbitrary precision classes: BigInteger, BigRational, BigFloat.
Illustrates working with prime numbers and the IntegerMath class in the Extreme.Mathematics namespace.
Illustrates how to compute the forward and inverse Fourier transform of a real or complex signal using classes in the Extreme.Mathematics.SignalProcessing namespace.
Illustrates how to write algorithms that are generic over the numerical type of the arguments.
Illustrates the basic numerical integration classes.
Illustrates more advanced numerical integration using the AdaptiveIntegrator class.
Higher Dimensional Numerical Integration
Illustrates numerical integration of functions in higher dimensions using classes in the Extreme.Mathematics.Calculus namespace.
Illustrates how to approximate the derivative of a function.
Illustrates integrating systems of ordinary differential equations (ODE's).
Illustrates the basic use of the Polynomial class .
Illustrates more advanced uses of the Polynomial class, including real and complex root finding, calculating least squares polynomials and polynomial arithmetic.
Illustrates the basic use of the ChebyshevSeries class .
Linear Curve Fitting
Illustrates how to fit linear combinations of curves to data using the LinearCurveFitter class and other classes in the Extreme.Mathematics.Curves namespace.
Nonlinear Curve Fitting
Illustrates nonlinear least squares curve fitting of predefined and user-defined curves using the NonlinearCurveFitter class.
Illustrates working with piecewise constant and piecewise linear curves using classes from the Extreme.Mathematics.Curves namespace.
Illustrates using natural and clamped cubic splines for interpolation using classes in the Extreme.Mathematics.LinearAlgebra namespace.
Newton-Raphson Equation Solver
Illustrates the use of the NewtonRaphsonSolver class for solving equations in one variable and related functions for numerical differentiation.
Root Bracketing Solvers
Illustrates the use of the root bracketing solvers for solving equations in one variable.
Illustrates the use of the NewtonRaphsonSystemSolver and DoglegSystemSolver classes for solving systems of nonlinear equations.
Optimization In One Dimension
Illustrates the use of the Brent and Golden Section optimizer classes in the Extreme.Mathematics.Optimization namespace for one-dimensional optimization.
Optimization In Multiple Dimensions
Illustrates the use of the multi-dimensional optimizer classes in the Extreme.Mathematics.Optimization namespace for optimization in multiple dimensions.
Illustrates solving linear programming (LP) problems using classes in the Extreme.Mathematics.Optimization.LinearProgramming namespace.
Mixed Integer Programming
Illustrates how to solve mixed integer programming by solving Sudoku puzzles using the linear programming solver.
Illustrates how to solve optimization problems a quadratic objective function and linear constraints using classes in the Extreme.Mathematics.Optimization namespace.
Illustrates solving nonlinear programs (optimization problems with linear or nonlinear constraints) using the NonlinearProgram and related classes.
Random Number Generators
Illustrates how to use specialized random number generator classes in the Extreme.Statistics.Random namespace.
Non-Uniform Random Numbers
Illustrates how to generate random numbers from a non-uniform distribution.
Illustrates how to generate quasi-random sequences like Fauré and Sobol sequences using classes in the Extreme.Statistics.Random namespace.
Illustrates the basic use of the Vector class for working with vectors.
Illustrates how to perform operations on Vector objects, including construction, element access, arithmetic operations.
Illustrates the basic use of the Matrix class for working with matrices.
Accessing Matrix Components
Illustrates different ways of iterating through the rows and columns of a matrix using classes in the Extreme.Mathematics.LinearAlgebra namespace.
Illustrates how to perform operations that involve both matrices and vectors.
Illustrates how to work efficiently with upper or lower triangular or trapezoidal matrices.
Illustrates how to work efficiently with symmetric matrices.
Illustrates how to work with the BandMatrix class.
Illustrates using sparse vectors and matrices using the classes in the Extreme.Mathematics.LinearAlgebra.Sparse namespace.
Illustrates how compute various decompositions of a matrix using classes in the Extreme.Mathematics.LinearAlgebra namespace.
Illustrates how to solve systems of simultaneous linear equations.
Structured Linear Equations
Illustrates how to solve systems of simultaneous linear equations that have special structure.
Iterative Sparse Solvers
Illustrates the use of iterative sparse solvers and preconditioners for efficiently solving large, sparse systems of linear equations.
Illustrates how to solve least squares problems using classes in the Extreme.Mathematics.LinearAlgebra namespace.
Illustrates how to use the classes that represent discrete probability distributions in the Extreme.Statistics.Distributions namespace.
Illustrates how to use the classes that represent continuous probability distributions in the Extreme.Statistics.Distributions namespace.
Illustrates how to use the OneWayAnovaModel class to perform a one-way analysis of variance.
Repeated Measures Anova
Illustrates how to use the OneWayRAnovaModel class to perform a one-way analysis of variance with repeated measures.
Illustrates how to use the TwoWayAnovaModel class to perform a two-way analysis of variance.
Illustrates how to perform a simple linear regression using the SimpleRegressionModel class.
Multiple Linear Regression
Illustrates how to use the LinearRegressionModel class to perform a multiple linear regression.
Illustrates how to fit data to polynomials using the PolynomialRegressionModel class.
Illustrates how to use the LogisticRegressionModel class to create logistic regression models.
Generalized Linear Models
Illustrates how to use the GeneralizedLinearModel class to compute probit, Poisson and similar regression models.
Simple Time Series
Illustrates how to perform simple operations on time series data using classes in the Extreme.Statistics.TimeSeriesAnalysis namespace.
Illustrates how to perform a range of transformations on statistical data.
Illustrates how to work with ARIMA time series models using classes in the Extreme.Statistics.TimeSeriesAnalysis namespace.
Illustrates how to use the classes in the Extreme.Statistics.Multivariate namespace to perform hierarchical clustering and K-means clustering.
Principal Component Analysis (PCA)
Illustrates how to perform a Principal Components Analysis using classes in the Extreme.Statistics.Multivariate namespace.
Factor Analysis (FA)
Illustrates how to perform a Factor Analysis using classes in the Extreme.Statistics.Multivariate namespace.
Illustrates how to use various tests for the mean of one or more sanples using classes in the Extreme.Statistics.Tests namespace.
Illustrates how to perform hypothesis tests involving the standard deviation or variance using classes in our .NET statistical library.
Illustrates how to test for goodness-of-fit using classes in the Extreme.Statistics.Tests namespace.
Homogeneity Of Variances Tests
Illustrates how to test a collection of variables for equal variances using classes in the Extreme.Statistics.Tests namespace.
Illustrates how to perform non-parametric tests like the Wilcoxon-Mann-Whitney test and the Kruskal-Wallis test.