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CenterSpace.NMath.Core Namespace

 
Classes
  ClassDescription
Public classAbstractRandomNumberStream
Class AbstractRandomNumberStream may be used to construct a RandomNumberStream object which uses a user defined function for the generation of uniformly distributed random numbers in the interval (0, 1).
Public classActiveSetLineSearchSQP
Class ActiveSetLineSearchSQP solves nonlinear programming problems using a Sequential Quadratic Programming (SQP) iterative algorithm.
Public classActiveSetLineSearchSQPOptions
Contains the options available to the ActiveSetLineSearchSQP Nonlinear Program Solver (NLP).
Public classActiveSetQPSolver
Class ActiveSetQPSolver solves convex quadratic programming (QP) problems.
Public classAnalysisFunctions
Class AnalysisFunctions provides common generalized functions for NMath Analysis.
Public classAnalysisFunctionsFiveParameterLogisticFtn
Computes the 5-parameter logistic (5PL) function, using the given vector of function parameters, at the specified point.
Public classAnalysisFunctionsFourParameterLogisticFtn
Computes the 4-parameter logistic (4PL) function, using the given vector of function parameters, at the specified point.
Public classAnalysisFunctionsThreeParameterExponentialFtn
Evaluates the three parameter exponential function for the given parameter values at the given point.
Public classAnalysisFunctionsThreeParameterSineFtn
Computes the three parameter sine function, using the given vector of function parameters, at the specified point.
Public classAnalysisFunctionsTwoParameterAsymptoticFtn
Computes the asymptotic function, using the given vector of function parameters, at the specified point.
Public classAnnealingHistory
Class AnnealingHistory encapsulates all of the data generated during a series of steps through an annealing schedule.
Public classAnnealingHistoryStep
Class AnnealingHistory.Step encapsulates all of the data associated with a step in an AnnealingHistory.
Public classAnnealingMinimizer
Class AnnealingMinimizer minimizes a multivariable function using the simulated annealing method.
Public classAnnealingScheduleBase
Class AnnealingScheduleBase is the abstract base class for annealing schedules.
Public classAnovaRegressionFactorParam
Class AnovaRegressionFactorParam provides information about a regression parameter associated with a specific level of an ANOVA factor.
Public classAnovaRegressionInteractionParam
Class AnovaRegressionInteractionParam provides information about a regression parameter associated with the interaction between the level of one ANOVA factor and the level of another ANOVA factor.
Public classAnovaRegressionParameter
Class AnovaRegressionParameter provides information about a regression parameter used to perform an analysis of variance by class TwoWayAnova.
Public classAnovaRegressionSubjectParam
Class AnovaRegressionSubjectParam provides information about a regression parameter associated with a subject dummy regression variable.
Public classArnoldiEigenvalueOptions
Options for solving symmetric eigenvalue problems using the shift and invert spectral transformation.
Public classArnoldiEigenvalueSolution
Class contianing solution information for an Arnoldi iteration eigenvalue problem.
Public classBairstowRootFinder
Class implementing Bairstows method finds roots for polynomials of degree greater than 3.
Public classBairstowRootFinderSolveResult
Class encapsulating information about the result of applying Bairstows method to a polynomial.
Public classBetaDistribution
Class BetaDistribution represents the beta probability distribution.
Public classBinomialDistribution
Class BinomialDistribution represents the discrete probability distribution of obtaining exactly n successes in N trials where the probability of success on each trial is P.
Public classBoundedMultiVariableFunctionFitterM
Class MultiVariableFunctionFitter< M > fits a parameterized multivariable function to a set of points where the parameters have inequality constraints.
Public classBoundedOneVariableFunctionFitterM
Class BoundedOneVariableFunctionFitter fits a parameterized one variable function to a set of points, where the functions parameters are constrained by upper and lower bounds.
Public classBoundedVariableProblem
Abstract class for representing a problem with bounded variables.
Public classBoxCox
Class for computing the Box-Cox power tranformations defined for a set of data points, {yi}, and parameter value lambda by yi(lambda) = (yi^lambda - 1)/lambda. In addition methods for computing the corresponding log-likelihood function and the value of lambda which maximizes it are provided.
Public classBoxCoxTransformation
Class BoxCoxTransformation performs a Box-Cox power transformation, which can be used to make non-normal data resemble normally-distributed data.
Public classBracket
Class Bracket searches in the downhill direction for two points that bracket a minimum of a univariate function.
Public classBrentMinimizer
Class BrentMinimizer uses Brent's Method to minimize a function within an interval known to contain a minimum.
Public classCentralDifferenceHessianUpdater
Class CentralDifferenceHessianUpdater updates the Hessian of the Lagrangian while solving a nonlinear programming problem using a Sequential Quadratic Programming algorithm.
Public classChiSquareDistribution
Class ChiSquareDistribution represents the chi-square probability distribution.
Public classClampedCubicSpline
Class ClampedCubicSpline represents a function determined by tabulated values. Function values are calculated using clamped cubic spline interpolation.
Public classClosedInterval
Class ClosedInterval represents a numeric interval with inclusive lower and upper bounds.
Public classClosedOpenInterval
Class ClosedOpenInterval represents a numeric interval with an inclusive lower bound and an exclusive upper bound.
Public classCode exampleClusterAnalysis
Class ClusterAnalysis perform hierarchical cluster analysis.
Public classClusterSet
Class ClusterSet represents a collection of objects assigned to a finite number of clusters.
Public classCode exampleCompressedSparseRowT
Class CompressedSparseRow stores general sparse matrix data in compressed row format.
Public classConjugateGradientMinimizer
Class ConjugateGradientMinimizer minimizes a multivariable function using the Polak-Ribiere variant of the Fletcher-Reeves conjugate gradient method.
Public classConnectivityMatrix
Class ConnectivityMatrix represents a symmetric matrix of double-precision floating point values.
Public classConstantSQPStepSize
Class ConstantSQPStepSize computes the step size for a Sequential Quadratic Programming solver. Simply returns a constant step size regardless of iteration values.
Public classConstrainedLeastSquares
Class for solver constrained least squares problems.
Public classConstrainedLeastSquaresProblem
Class that encapsulates a constrained least squares problem.
Public classConstrainedOptimizer
Base class for linear Microsoft Solver Foundation based linear solvers.
Public classConstrainedOptimizerORTools
Base class for linear Google OR-Tools based linear solvers.
Public classConstraint
Class Constraint represents a constraint in a constrained optimization problem.
Public classConvolutionBase
Abstract base class for all concrete convolution classes.
Public classCORegressionCalculation
Class CORegressionCalculation computes linear regression parameters by the method of least squares using a complete orthogonal decomposition.
Public classCorrelationBase
Abstract base class for all concrete correlation classes.
Public classCorrelationFilter
The base correlation filter which provides basic correlation services.
Public classCubicSpline
Class CublicSpline represents a function whose values are determined by cubic spline interpolation between tabulated values.
Public classCurveFitDataSet
Class for aggregating data used in curve fitting. Contains x-values with their corresponding y-values along with with weights to be applied to the y-values during curve fitting.
Public classCustomAnnealingSchedule
Class CustomAnnealingSchedule encapsulates a series of iterations and temperatures.
Public classDampedBFGSHessianUpdater
Class DampedBFGSHessianUpdater updates the value of the Lagrangian Hessian based on iterate values using a quasi-Newton approximation.
Public classDataFrame
Class DataFrame represents a two-dimensional data object consisting of a list of columns of the same length.
Public classDBrentMinimizer
Class DBrentMinimizer minimizes a function using Brent's method as well as the first derivative.
Public classDFBoolColumn
Class DFBoolColumn represents a column of logical data in a data frame.
Public classDFColumn
Abstract base class for data frame column types.
Public classDFDateTimeColumn
Class DFDataTimeColumn represents a column of DataTime data in a data frame.
Public classDFGenericColumn
Class DFGenericColumn represents a column of generic data in a data frame.
Public classDFIntColumn
Class DFIntColumn represents a column of integer data in a data frame.
Public classDFNumericColumn
Class DFNumericColumn represents a column of numeric data in a data frame.
Public classDFStringColumn
Class DFStringColumn represents a column of string data in a data frame.
Public classDiscreteDataIntegrator
Integrates discrete data for either unit-spaced or arbitrarily spaced data.
Public classDiscreteWaveletTransform
This abstract class represents all discrete wavelet transforms objects.
Public classDistance
Class Distance provides functions for computing the distance between objects.
Public classDistancePowerDistance
Class PowerDistance compute the power distance between two vectors.
Public classCode exampleDouble1DConvolution
Double1DConvolution represents a 1D convolution, with a specified kernel and data length.
Public classCode exampleDouble1DCorrelation
Double1DCorrelation represents a 1D correlation, with a specified kernel and data length.
Public classDoubleBandFact
Class DoubleBandFact represents the factorization of a banded matrix of double-precision floating point numbers.
Public classDoubleBandMatrix
Class DoubleBandMatrix represents a banded matrix of double-precision floating point values. A banded matrix is a matrix that has all its non-zero entries near the diagonal.
Public classDoubleBisquareWeightingFunction
Class DoubleBisquareWeightingFunction implements the bisquare weighting function for Iteratively Reweighted Least Squares (IRLS).
Public classDoubleCholeskyLeastSq
Class DoubleCholeskyLeastSq solves least square problems by using the Cholesky factorization to solve the normal equations.
Public classCode exampleDoubleComplex1DConvolution
DoubleComplex1DConvolution represents a 1D convolution, with a specified kernel and data length.
Public classCode exampleDoubleComplex1DCorrelation
DoubleComplex1DCorrelation represents a 1D correlation, with a specified kernel and data length.
Public classDoubleComplexBackward1DFFT
DoubleComplexBackward1DFFT represents the backward discrete fourier transform of a 1D complex signal vector.
Public classDoubleComplexBackward2DFFT
DoubleComplexBackward2DFFT represents the backward discrete fourier transform of a 2D complex signal vector.
Public classDoubleComplexBandFact
Class DoubleComplexBandFact represents the factorization of a banded matrix of complex double-precision floating point numbers.
Public classDoubleComplexBandMatrix
Class DoubleComplexBandMatrix represents a banded matrix of double-precision complex numbers. A banded matrix is a matrix that has all its non-zero entries near the diagonal.
Public classDoubleComplexCholeskyLeastSq
Class DoubleComplexCholeskyLeastSq solves least square problems by using the Cholesky factorization to solve the normal equations.
Public classDoubleComplexCsrSparseMatrix
Class DoubleComplexCsrSparseMatrix stores a general sparse matrix using Compressed Row (CSR) Storage format.
Public classDoubleComplexDataBlock
The DoubleComplexDataBlock struct defines a contiguous subset of an array of DoubleComplex numbers. A DoubleComplexDataBlock instance contains a reference to an array and an offset into the array.
Public classDoubleComplexEigDecomp
Class DoubleComplexEigDecomp computes the eigenvalues and left and right eigenvectors of a general matrix, with preliminary balancing.
Public classDoubleComplexEigDecompServer
Class DoubleComplexEigDecompServer creates eigenvalue decompositions. A server instance can be configured to perform preliminary balancing, and to compute left eigenvectors, right eigenvectors, both, or neither.
Public classDoubleComplexForward1DFFT
DoubleComplexForward1DFFT represents the forward discrete fourier transform of a 1D complex signal vector.
Public classDoubleComplexForward2DFFT
DoubleComplexForward2DFFT represents the forward discrete fourier transform of a 2D complex signal vector.
Public classDoubleComplexGSVDecomp
Class DoubleComplexGSVDecomp computes the generalized singular value decomposition (GSVD) of a pair of general rectangular matrices.
Public classDoubleComplexGSVDecompServer
Class for serving up generalized singular value decompositions (GSVD) in the form of DoubleComplexGSVDecomp instances.
Public classDoubleComplexLeastSquares
Class DoubleComplexLeastSquares computes the minimum-norm solution to a linear system Ax = y.
Public classDoubleComplexLowerTriMatrix
Class DoubleComplexLowerTriMatrix represents a lower triangular matrix of double-precision complex numbers. A lower triangular matrix is a square matrix with all elements above the main diagonal equal to zero.
Public classDoubleComplexLUFact
Class DoubleComplexLUFact represents the LU factorization of a matrix of DoubleComplex numbers.
Public classDoubleComplexMatrix
Class DoubleComplexMatrix represents a general mathematical matrix class of DoubleComplex numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.
Public classDoubleComplexQRDecomp
Class DoubleComplexQRDecomp represents the QR decomposition of a general matrix.
Public classDoubleComplexQRDecompServer
Class DoubleComplexQRDecompServer allows control over how the pivoting is done in the creation of DoubleComplexQRDecomp objects.
Public classDoubleComplexQRLeastSq
Class DoubleComplexQRLeastSq solves least squares problems by using a QR decomposition.
Public classDoubleComplexSparseFact
Class DoubleComplexSparseFact performs general sparse matrix factorizations.
Public classDoubleComplexSparseVector
Class DoubleComplexSparseVector encapsulates a general sparse vector.
Public classDoubleComplexSVDecomp
Class DoubleComplexSVDecomp represents the singular value decomposition (SVD) of a matrix.
Public classDoubleComplexSVDecompServer
Class DoubleComplexSVDecompServer constructs instances of the DoubleComplexSVDecomp class.
Public classDoubleComplexSVDLeastSq
Class DoubleComplexSVDLeastSq solves least squares problems by using a singular value decomposition.
Public classDoubleComplexTriDiagFact
Class DoubleComplexTriDiagFact represents the LU factorization of a tridiagonal matrix of double-precision complex floating point numbers.
Public classDoubleComplexTriDiagMatrix
Class DoubleComplexTriDiagMatrix represents a tridiagonal matrix of double-precision complex numbers. A tridiagonal matrix is a matrix which has all its non-zero entries on the main diagonal, the super diagonal, and the subdiagonal.
Public classDoubleComplexUpperTriMatrix
Class DoubleComplexComplexUpperTriMatrix represents an upper triangular matrix of double-precision complex numbers. An upper triangular matrix is a square matrix with all elements below the main diagonal equal to zero.
Public classDoubleComplexVector
Class DoubleComplexVector represents a mathematical vector of DoubleComplex numbers.
Public classDoubleCOWeightedLeastSq
Class DoubleCOWeightedLeastSq solves weighted least squares problems by using a Complete Orthogonal (CO) decomposition technique.
Public classDoubleCsrSparseMatrix
Class DoubleCsrSparseMatrix stores a general sparse matrix using Compressed Row (CSR) storage format.
Public classDoubleDataBlock
The DoubleDataBlock struct defines a contiguous subset of an array of double-precision floating point numbers. A DoubleDataBlock instance contains a reference to an array and an offset into the array.
Public classDoubleDWT
This class represents a double precision discrete wavelet transform. It supports both single step forward and reverse DWT's and multilevel signal deconstruction and reconstruction. Details thresholding at any level and threshold calculations are also supported.
Public classDoubleEigDecomp
Class DoubleEigDecomp computes the eigenvalues and left and right eigenvectors of a general matrix, with preliminary balancing.
Public classDoubleEigDecompServer
Class DoubleEigDecompServer creates eigenvalue decompositions. A server instance can be configured to perform preliminary balancing, and to compute left eigenvectors, right eigenvectors, both, or neither.
Public classDoubleFactorAnalysisExtraction, Rotation
Class
DoubleFactorAnalysis
performs a factor analysis on a symmetric matrix of data, assumed to be either a correlation or covariance matrix, using specified factor extraction and rotation algorithms. The analysis consists of 2 steps: First, factors are extracted from the symmetric matrix data, second, the factors are rotated in order to maximize the relationship between the variables and some of the factors.
Public classDoubleFairWeightingFunction
Class DoubleFairWeightingFunction implements the fair weighting function for Iteratively Reweighted Least Squares (IRLS).
Public classCode exampleDoubleForward1DFFT
DoubleForward1DFFT represents the forward discrete fourier transform of a 1D real signal vector.
Public classDoubleForward2DFFT
DoubleForward2DFFT represents the forward discrete fourier transform of a 2D real signal vector.
Public classDoubleFunctional
Class DoubleFunctional represents a double precision functional.
Public classDoubleFunctionalDelegate
Class DoubleFunctionalDelegate wraps a functional delegate specified by a delegate in a DoubleFunctional object.
Public classCode exampleDoubleGeneral1DFFT
General 1D FFT class assuming the behavior of the provided FFT configuration instance.
Public classDoubleGSVDecomp
Class DoubleGSVDecomp computes the generalized singular value decomposition (GSVD) of a pair of general rectangular matrices.
Public classDoubleGSVDecompServer
Class for serving up generalized singular value decompositions (GSVD) in the form of DoubleGSVDecomp instances.
Public classDoubleHermCsrSparseMatrix
Class DoubleHermCsrSparseMatrix stores a general sparse Hermitian matrix using the Compressed Row (CSR) storage format.
Public classDoubleHermitianBandMatrix
Class DoubleHermitianBandMatrix represents an Hermitian banded matrix of double-precision floating point values. An Hermitian banded matrix is an Hermitian matrix that has all its non-zero entries near the diagonal.
Public classDoubleHermitianEigDecomp
Class DoubleHermitianEigDecomp computes the eigenvalues and eigenvectors of a symmetrix matrix.
Public classDoubleHermitianEigDecompServer
Class DoubleHermitianEigDecompServer creates eigenvalue decompositions. A server instance can be configured to compute eigenvalues only, or both eigenvalues and eigenvectors. In addition, the server can be configured to compute only the eigenvalues in a given range. A tolerance for the convergence of the algorithm may also be specified.
Public classDoubleHermitianFact
Class DoubleHermitianFact represents the factorization of a Hermitian, matrix of complex double-precision floating point numbers.
Public classDoubleHermitianMatrix
Class DoubleHermitianMatrix represents a matrix of double-precision floating point complex values.
Public classDoubleHermitianPDBandFact
Class DoubleHermitianPDBandFact represents the factorization of a Hermitian, positive definite, banded matrix of complex double-precision floating point numbers.
Public classDoubleHermitianPDFact
Class DoubleHermitianPDFact represents the Cholesky factorization of a Hermitian, positive definite, matrix of double-precision complex floating point numbers. In a Cholesky factorization a Hermitian, positive definite matrix A is factored as A = UU' where U is upper triangular and U' is the conjugate transpose of U.
Public classDoubleHermPDTriDiagFact
Class DoubleHermPDTriDiagFact represents the LDL' factorization of a Hermitian, positive definite, tridiagonal matrix of complex double-precision floating point numbers.
Public classDoubleIterativelyReweightedLeastSq
Class DoubleIterativelyReweightedLeastSq solves a least squares problems by iteratively applying a weighted least squares fit.
Public classDoubleLeastSquares
Class DoubleLeastSquares computes the minimum-norm solution to a linear system Ax = y.
Public classDoubleLeastSqWeightingFunction
Abstract base class for least squares weighting functions used in the Iteratively Reweighted Least Squares algorithm.
Public classDoubleLowerTriMatrix
Class DoubleLowerTriMatrix represents a lower triangular matrix of double-precision floating point values. A lower triangular matrix is a square matrix with all elements above the main diagonal equal to zero.
Public classDoubleLUFact
Class DoubleLUFact represents the LU factorization of a matrix of double-precision floating point numbers.
Public classDoubleMatrix
Class DoubleMatrix represents a general mathematical matrix class of double-precision floating point numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.
Public classDoubleMultiVariableFunction
Abstract class for representing a multi-variable function.
Public classDoubleNonnegativeLeastSqResult
Class containing the results of a nonnegative least squares solve attempt. Double precision version.
Public classDoubleNonnegativeLeastSquares
Class DoubleNonnegativeLeastSquares computes the minimum-norm solution to a linear system Ax = y subject to the constraint that all the elements, x[i], are nonnegative.
Public classDoubleParameterizedDelegate
Class which creates a DoubleParameterizedFunction instance from delegates.
Public classDoubleParameterizedFunction
Abstract class representing a parameterized function.
Public classDoubleParameterizedFunctional
Abstract class representing a parameterized functional.
Public classDoublePCA
Class DoublePCA performs a principal component analysis on a given double-precision data matrix, or data frame.
Public classDoubleQRDecomp
Class DoubleQRDecomp represents the QR decomposition of a general matrix.
Public classDoubleQRDecompServer
Class DoubleQRDecompServer allows control over how the pivoting is done in the creation of DoubleQRDecomp objects.
Public classDoubleQRLeastSq
Class DoubleQRLeastSq solves least squares problems by using a QR decomposition.
Public classDoubleRandomBetaDistribution
Class DoubleRandomBetaDistribution generates random numbers from a beta distribution.
Public classDoubleRandomCauchyDistribution
Class DoubleRandomCauchyDistribution generates random numbers from a Cauchy distribution.
Public classDoubleRandomExponentialDistribution
Class DoubleRandomExponentialDistribution generates random numbers from an exponential distribution.
Public classDoubleRandomGammaDistribution
Class DoubleRandomGammaDistribution generates random numbers from a gamma distribution.
Public classDoubleRandomGaussianDistribution
Class DoubleRandomGaussianDistribution generates random numbers from a Gaussian distribution.
Public classDoubleRandomGumbelDistribution
Class DoubleRandomGumbelDistribution generates random numbers from a Gumbel distribution.
Public classDoubleRandomLaplaceDistribution
Class DoubleRandomLaplaceDistribution generates random numbers from a Laplace distribution.
Public classDoubleRandomLogNormalDistribution
Class DoubleRandomLogNormalDistribution generates random numbers from a lognormal distribution.
Public classDoubleRandomRayleighDistribution
Class DoubleRandomRayleighDistribution generates random numbers from an Rayleigh distribution.
Public classDoubleRandomUniformDistribution
Class DoubleRandomUniformDistribution generates random numbers uniformly distributed over an interval.
Public classDoubleRandomWeibullDistribution
Class DoubleRandomWeibullDistribution generates random numbers from a Weibull distribution.
Public classDoubleSparseFact
Class DoubleSparseFact performs general sparse matrix factorizations.
Public classDoubleSparseHermFact
Class DoubleSparseHermFact performs Hermitian sparse matrix factorizations.
Public classDoubleSparseHermPDFact
Class DoubleSparseHermPDFact performs sparse Hermitian Positive Definite matrix factorizations.
Public classDoubleSparseSymFact
Class DoubleSparseSymFact performs sparse symmetric matrix factorizations.
Public classDoubleSparseSymPDFact
Class DoubleSparseSymPDFact performs sparse positive definite symmetric matrix factorizations.
Public classDoubleSparseVector
Class DoubleSparseVector encapsulates a general sparse vector.
Public classDoubleSVDecomp
Class DoubleSVDecomp represents the singular value decomposition (SVD) of a matrix.
Public classDoubleSVDecompServer
Class DoubleSVDecompServer constructs instances of the DoubleSVDecomp class.
Public classDoubleSVDLeastSq
Class DoubleSVDLeastSq solves least squares problems by using a singular value decomposition.
Public classDoubleSymBandMatrix
Class DoubleSymBandMatrix represents a symmetric banded matrix of double-precision floating point values. A symmetric banded matrix is a symmetric matrix that has all its non-zero entries near the diagonal.
Public classDoubleSymCsrSparseMatrix
Class DoubleSymCsrSparseMatrix stores a sparse symmetric matrix using the CompreSsed Row (CSR) storage format.
Public classDoubleSymEigDecomp
Class DoubleSymEigDecomp computes the eigenvalues and eigenvectors of a symmetrix matrix.
Public classDoubleSymEigDecompServer
Class DoubleSymEigDecompServer creates eigenvalue decompositions. A server instance can be configured to compute eigenvalues only, or both eigenvalues and eigenvectors. In addition, the server can be configured to compute only the eigenvalues in a given range. A tolerance for the convergence of the algorithm may also be specified.
Public classDoubleSymFact
Class DoubleSymFact represents the factorization of a symmetric, matrix of double-precision floating point numbers.
Public classCode exampleDoubleSymmetric2DSignalReader
Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 2D FFT's of real signals.
Public classDoubleSymmetricBackward1DFFT
DoubleSymmetricBackward1DFFT represents the backward discrete fourier transform of a 1D real signal vector, and inverses packed conjugate symmetric signals back to the real domain.
Public classDoubleSymmetricMatrix
Class DoubleSymmetricMatrix represents a symmetric matrix of double-precision floating point values.
Public classCode exampleDoubleSymmetricSignalReader
Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 1D FFT's of real signals.
Public classDoubleSymPDBandFact
Class DoubleSymPDBandFact represents the factorization of a symmetric, positive definite, banded matrix of double-precision floating point numbers.
Public classDoubleSymPDFact
Class DoubleSymPDFact represents the Cholesky factorization of a symmetric, positive definite, matrix of double-precision floating point numbers. In a Cholesky factorization a symmetric, positive definite matrix A is factored as A = UU' where U is upper triangular and U' is the transpose of U.
Public classDoubleSymPDTriDiagFact
Class DoubleSymPDTriDiagFact represents the LDL' factorization of a symmetric, positive definite, tridiagonal matrix of double-precision floating point numbers.
Public classDoubleTriDiagFact
Class DoubleTriDiagFact represents the LU factorization of a tridiagonal matrix of double-precision floating point numbers.
Public classDoubleTriDiagMatrix
Class DoubleTriDiagMatrix represents a tridiagonal matrix of double-precision floating point values. A tridiagonal matrix is a matrix which has all its non-zero entries on the main diagonal, the super diagonal, and the subdiagonal.
Public classDoubleUpperTriMatrix
Class DoubleUpperTriMatrix represents an upper triangular matrix of double-precision floating point values. An upper triangular matrix is a square matrix with all elements below the main diagonal equal to zero.
Public classDoubleVector
Class DoubleVector represents a mathematical vector of double-precision floating point numbers.
Public classDoubleVectorParameterizedDelegate
Class DoubleVectorParameterizedDelegate creates a DoubleParameterizedFunctional instance from delegates.
Public classCode exampleDoubleWavelet
This class represents a double precision wavelet. There are fives types of built in wavelets avaiable: Harr, Daubechies, Least Asymmetric, Best Localized, and Coiflet. User generated wavelets can be created by provided the low-pass decimation filter parameters in the constructor.
Public classDownhillSimplexMinimizer
Class DownhillSimplexMinimizer minimizes a multivariable function using the downhill simplex method of Nelder and Mead.
Public classDualSimplexSolver Obsolete.
Class DualSimplexSolver is a class for solving linear programming prolems using the dual simplex method.
Public classDualSimplexSolverORTools
Class DualSimplexSolverORTools is a class for solving linear programming prolems using the dual simplex method.
Public classDualSimplexSolverParams Obsolete.
Dual simplex algorithm parameters.
Public classEqualityConstrainedQPProblem
Class representing an equality constrained Quadratic Programming problem. Minimize 0.5 * x'Hx + x'c Subject to Ax = b where x is a vector of unknows, H a symmetric matrix, and A matrix.
Public classExponentialDistribution
Class ExponentialDistribution represents the Exponential probability distribution.
Public classFactor
Class Factor represents a categorical vector in which all elements are drawn from a finite number of factor levels.
Public classFactorAnalysisCorrelationExtraction, Rotation
Class FactorAnalysisCorrelation performs a factor analysis on a set of case data using the correlation matrix and specified factor extraction and rotation algorithms.
Public classFactorAnalysisCovarianceExtraction, Rotation
Class FactorAnalysisCovariance performs a factor analysis on a set of case data using the covariance matrix and specified factor extraction and rotation algorithms.
Public classFDistribution
Class FDistribution represents the F probability distribution.
Public classFFT2DBase
Abstract base class for all 2D discrete FFT transform classes. This class manages the setup and tear down of all discrete fourier resources.
Public classFFTBase
Abstract base class for all 1D discrete FFT transform classes. This class manages the setup and tear down of all discrete fourier resources.
Public classFFTConfiguration
FFTConfiguration contains all of the FFT configuration state to efficiently compute a FFT. This class is typically used in conjunction with the GeneralxDFFT set of classes to configure FFT's with offset and strided signal data.
Public classFFTKernelException
Exception thrown when MKL or CUDA returns an error condition when computing a FFT
Public classCode exampleFloat1DConvolution
Float1DConvolution represents a 1D convolution, with a specified kernel and data length.
Public classCode exampleFloat1DCorrelation
Float1DCorrelation represents a 1D correlation, with a specified kernel and data length.
Public classFloatBandFact
Class FloatBandFact represents the factorization of a banded matrix of single-precision floating point numbers.
Public classFloatBandMatrix
Class FloatBandMatrix represents a banded matrix of single-precision floating point values. A banded matrix is a matrix that has all its non-zero entries near the diagonal.
Public classFloatCholeskyLeastSq
Class FloatCholeskyLeastSq solves least square problems by using the Cholesky factorization to solve the normal equations.
Public classCode exampleFloatComplex1DConvolution
FloatComplex1DConvolution represents a 1D convolution, with a specified kernel and data length.
Public classCode exampleFloatComplex1DCorrelation
FloatComplex1DCorrelation represents a 1D correlation, with a specified kernel and data length.
Public classFloatComplexBackward1DFFT
FloatComplexBackward1DFFT represents the backward discrete fourier transform of a 1D complex signal vector.
Public classFloatComplexBackward2DFFT
FloatComplexBackward2DFFT represents the backward discrete fourier transform of a 2D complex signal vector.
Public classFloatComplexBandFact
Class FloatComplexBandFact represents the factorization of a banded matrix of complex single-precision floating point numbers.
Public classFloatComplexBandMatrix
Class FloatComplexBandMatrix represents a banded matrix of single-precision complex numbers. A banded matrix is a matrix that has all its non-zero entries near the diagonal.
Public classFloatComplexCholeskyLeastSq
Class FloatComplexCholeskyLeastSq solves least square problems by using the Cholesky factorization to solve the normal equations.
Public classFloatComplexCsrSparseMatrix
Class FloatComplexCsrSparseMatrix stores a general sparse matrix using Compressed Row (CSR) Storage format.
Public classFloatComplexDataBlock
The FloatComplexDataBlock struct defines a contiguous subset of an array of FloatComplex numbers. A FloatComplexDataBlock instance contains a reference to an array and an offset into the array.
Public classFloatComplexEigDecomp
Class FloatComplexEigDecomp computes the eigenvalues and left and right eigenvectors of a general matrix, with preliminary balancing.
Public classFloatComplexEigDecompServer
Class FloatComplexEigDecompServer creates eigenvalue decompositions. A server instance can be configured to perform preliminary balancing, and to compute left eigenvectors, right eigenvectors, both, or neither.
Public classFloatComplexForward1DFFT
FloatComplexForward1DFFT represents the forward discrete fourier transform of a 1D complex signal vector.
Public classFloatComplexForward2DFFT
FloatComplexForward2DFFT represents the forward discrete fourier transform of a 2D complex signal vector.
Public classFloatComplexGSVDecomp
Class FloatComplexGSVDecomp computes the generalized singular value decomposition (GSVD) of a pair of general rectangular matrices.
Public classFloatComplexGSVDecompServer
Class for serving up generalized singular value decompositions (GSVD) in the form of FloatComplexGSVDecomp instances.
Public classFloatComplexLeastSquares
Class FloatComplexLeastSquares computes the minimum-norm solution to a linear system Ax = y.
Public classFloatComplexLowerTriMatrix
Class FloatComplexLowerTriMatrix represents a lower triangular matrix of single-precision complex numbers. A lower triangular matrix is a square matrix with all elements above the main diagonal equal to zero.
Public classFloatComplexLUFact
Class FloatComplexFact represents the LU factorization of a matrix of FloatComplex numbers.
Public classFloatComplexMatrix
Class FloatComplexMatrix represents a general mathematical matrix class of FloatComplex numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.
Public classFloatComplexQRDecomp
Class FloatComplexQRDecomp represents the QR decomposition of a general matrix.
Public classFloatComplexQRDecompServer
Class FloatComplexQRDecompServer allows control over how the pivoting is done in the creation of FloatComplexQRDecomp objects.
Public classFloatComplexQRLeastSq
Class FloatComplexQRLeastSq solves least squares problems by using a QR decomposition.
Public classFloatComplexSparseFact
Class FloatComplexSparseFact performs general sparse matrix factorizations.
Public classFloatComplexSparseVector
Class FloatComplexSparseVector encapsulates a general sparse vector.
Public classFloatComplexSVDecomp
Class FloatComplexSVDecomp represents the singular value decomposition (SVD) of a matrix.
Public classFloatComplexSVDecompServer
Class FloatComplexSVDecompServer constructs instances of the FloatComplexSVDecomp class.
Public classFloatComplexSVDLeastSq
Class FloatComplexSVDLeastSq solves least squares problems by using a singular value decomposition.
Public classFloatComplexTriDiagFact
Class FloatComplexTriDiagFact represents the LU factorization of a tridiagonal matrix of single-precision complex floating point numbers.
Public classFloatComplexTriDiagMatrix
Class FloatComplexTriDiagMatrix represents a tridiagonal matrix of single-precision complex numbers. A tridiagonal matrix is a matrix which has all its non-zero entries on the main diagonal, the super diagonal, and the subdiagonal.
Public classFloatComplexUpperTriMatrix
Class FloatComplexUpperTriMatrix represents an upper triangular matrix of single-precision complex numbers. An upper triangular matrix is a square matrix with all elements below the main diagonal equal to zero.
Public classFloatComplexVector
Class FloatComplexVector represents a mathematical vector of FloatComplex numbers.
Public classFloatCsrSparseMatrix
Class FloatCsrSparseMatrix stores a general sparse matrix using Compressed Row (CSR) storage format.
Public classFloatDataBlock
The FloatDataBlock struct defines a contiguous subset of an array of floating point numbers. A FloatDataBlock instance contains a reference to an array, and an offset into the array.
Public classFloatDWT
This class represents a single precision discrete wavelet transform. It supports both single step forward and reverse DWT's and multilevel signal deconstruction and reconstruction. Details thresholding at any level and threshold calculations are also supported.
Public classFloatEigDecomp
Class FloatEigDecomp computes the eigenvalues and left and right eigenvectors of a general matrix, with preliminary balancing.
Public classFloatEigDecompServer
Class FloatEigDecompServer creates eigenvalue decompositions. A server instance can be configured to perform preliminary balancing, and to compute left eigenvectors, right eigenvectors, both, or neither.
Public classCode exampleFloatForward1DFFT
FloatForward1DFFT represents the forward discrete fourier transform of a 1D real signal vector.
Public classFloatForward2DFFT
FloatForward2DFFT represents the forward discrete fourier transform of a 2D real signal vector.
Public classCode exampleFloatGeneral1DFFT
General 1D FFT class assuming the behavior of the provided FFT configuration instance.
Public classFloatGSVDecomp
Class FloatGSVDecomp computes the generalized singular value decomposition (GSVD) of a pair of general rectangular matrices.
Public classFloatGSVDecompServer
Class for serving up generalized singular value decompositions (GSVD) in the form of FloatGSVDecomp instances.
Public classFloatHermCsrSparseMatrix
Class FloatHermCsrSparseMatrix stores a general sparse Hermitian matrix using the Compressed Row (CSR) storage format.
Public classFloatHermitianBandMatrix
Class FloatHermitianBandMatrix represents an Hermitian banded matrix of double-precision floating point values. An Hermitian banded matrix is an Hermitian matrix that has all its non-zero entries near the diagonal.
Public classFloatHermitianEigDecomp
Class FloatHermitianEigDecomp computes the eigenvalues and eigenvectors of a symmetrix matrix.
Public classFloatHermitianEigDecompServer
Class FloatHermitianEigDecompServer creates eigenvalue decompositions. A server instance can be configured to compute eigenvalues only, or both eigenvalues and eigenvectors. In addition, the server can be configured to compute only the eigenvalues in a given range. A tolerance for the convergence of the algorithm may also be specified.
Public classFloatHermitianFact
Class FloatHermitianFact represents the factorization of a Hermitian, matrix of complex single-precision floating point numbers.
Public classFloatHermitianMatrix
Class FloatHermitianMatrix represents a matrix of single-precision floating point complex values.
Public classFloatHermitianPDBandFact
Class FloatHermitianPDBandFact represents the factorization of a Hermitian, positive definite, banded matrix of complex single-precision floating point numbers.
Public classFloatHermitianPDFact
Class FloatHermitianPDFact represents the Cholesky factorization of a Hermitian, positive definite, matrix of single-precision complex floating point numbers. In a Cholesky factorization a Hermitian, positive definite matrix A is factored as A = UU' where U is upper triangular and U' is the conjugate transpose of U.
Public classFloatHermPDTriDiagFact
Class FloatHermPDTriDiagFact represents the LDL' factorization of a Hermitian, positive definite, tridiagonal matrix of complex single-precision floating point numbers.
Public classFloatLeastSquares
Class FloatLeastSquares computes the minimum-norm solution to a linear system Ax = y.
Public classFloatLowerTriMatrix
Class FloatLowerTriMatrix represents a lower triangular matrix of single-precision floating point values. A lower triangular matrix is a square matrix with all elements above the main diagonal equal to zero.
Public classFloatLUFact
Class FloatLUFact represents the LU factorization of a matrix of floating point numbers.
Public classFloatMatrix
Class FloatMatrix represents a general mathematical matrix class of floating point numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.
Public classFloatNonnegativeLeastSqResult
Class containing the results of a nonnegative least squares solve attempt. Single precision version.
Public classFloatNonnegativeLeastSquares
Class FloatNonnegativeLeastSquares computes the minimum-norm solution to a linear system Ax = y subject to the constraint that all the elements, x[i], are nonnegative.
Public classFloatPCA
Class FloatPCA performs a principal component analysis on a given single-precision data matrix.
Public classFloatQRDecomp
Class FloatQRDecomp represents the QR decomposition of a general matrix.
Public classFloatQRDecompServer
Class FloatQRDecompServer allows control over how the pivoting is done in the creation of FloatQRDecomp objects.
Public classFloatQRLeastSq
Class FloatQRLeastSq solves least squares problems by using a QR decomposition.
Public classFloatRandomBetaDistribution
Class FloatRandomBetaDistribution generates random numbers from a beta distribution.
Public classFloatRandomCauchyDistribution
Class FloatRandomCauchyDistribution generates random numbers from a Cauchy distribution.
Public classFloatRandomExponentialDistribution
Class FloatRandomExponentialDistribution generates random numbers from an exponential distribution.
Public classFloatRandomGammaDistribution
Class FloatRandomGammaDistribution generates random numbers from a gamma distribution.
Public classFloatRandomGaussianDistribution
Class FloatRandomGaussianDistribution generates random numbers from a Gaussian distribution.
Public classFloatRandomGumbelDistribution
Class FloatRandomGumbelDistribution generates random numbers from a Gumbel distribution.
Public classFloatRandomLaplaceDistribution
Class FloatRandomLaplaceDistribution generates random numbers from a Laplace distribution.
Public classFloatRandomLogNormalDistribution
Class FloatRandomLogNormalDistribution generates random numbers from a lognormal distribution.
Public classFloatRandomRayleighDistribution
Class FloatRandomRayleighDistribution generates random numbers from an Rayleigh distribution.
Public classFloatRandomUniformDistribution
Class DoubleRandomUniformDistribution generates random numbers uniformly distributed over an interval.
Public classFloatRandomWeibullDistribution
Class FloatRandomWeibullDistribution generates random numbers from a Weibull distribution.
Public classFloatSparseFact
Class FloatSparseFact performs general sparse matrix factorizations.
Public classFloatSparseHermFact
Class FloatSparseHermFact performs Hermitian sparse matrix factorizations.
Public classFloatSparseHermPDFact
Class FloatSparseHermPDFact performs sparse Hermitian Positive Definite matrix factorizations.
Public classFloatSparseSymFact
Class FloatSparseSymFact performs sparse symmetric matrix factorizations.
Public classFloatSparseSymPDFact
Class FloatSparseSymPDFact performs sparse positive definite symmetric matrix factorizations.
Public classFloatSparseVector
Class FloatSparseVector encapsulates a general sparse vector.
Public classFloatSVDecomp
Class FloatSVDecomp represents the singular value decomposition (SVD) of a matrix.
Public classFloatSVDecompServer
Class FloatSVDecompServer constructs instances of the FloatSVDecomp class.
Public classFloatSVDLeastSq
Class FloatSVDLeastSq solves least squares problems by using a singular value decomposition.
Public classFloatSymBandMatrix
Class FloatSymBandMatrix represents a symmetric banded matrix of single-precision floating point values. A symmetric banded matrix is a symmetric matrix that has all its non-zero entries near the diagonal.
Public classFloatSymCsrSparseMatrix
Class FloatSymCsrSparseMatrix stores a sparse symmetric matrix using the CompreSsed Row (CSR) storage format.
Public classFloatSymEigDecomp
Class FloatSymEigDecomp computes the eigenvalues and eigenvectors of a symmetrix matrix.
Public classFloatSymEigDecompServer
Class FloatSymEigDecompServer creates eigenvalue decompositions. A server instance can be configured to compute eigenvalues only, or both eigenvalues and eigenvectors. In addition the server can be configured to compute only the eigenvalues in a given range. A tolerance for the convergence of the algorithm may also be specified.
Public classFloatSymFact
Class FloatSymFact represents the factorization of a symmetric matrix of single-precision floating point numbers.
Public classCode exampleFloatSymmetric2DSignalReader
Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 2D FFT's of real signals.
Public classFloatSymmetricBackward1DFFT
FloatSymmetricBackward1DFFT represents the backward discrete fourier transform of a 1D real signal vector. This class and inverts packed conjugate symmetric signals in the freqency domain back to the real domain.
Public classFloatSymmetricMatrix
Class FloatSymmetricMatrix represents a symmetric matrix of float-precision floating point values.
Public classCode exampleFloatSymmetricSignalReader
Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 1D FFT's of real signals.
Public classFloatSymPDBandFact
Class FloatSymPDBandFact represents the factorization of a symmetric, positive definite, banded matrix of single-precision floating point numbers.
Public classFloatSymPDFact
Class FloatSymPDFact represents the Cholesky factorization of a symmetric, positive definite, matrix of single-precision floating point numbers. In a Cholesky factorization a symmetric, positive definite matrix A is factored as A = UU' where U is upper triangular and U' is the transpose of U.
Public classFloatSymPDTriDiagFact
Class FloatSymPDTriDiagFact represents the LDL' factorization of a symmetric, positive definite, tridiagonal matrix of single-precision floating point numbers.
Public classFloatTriDiagFact
Class FloatTriDiagFact represents the LU factorization of a tridiagonal matrix of single-precision floating point numbers.
Public classFloatTriDiagMatrix
Class FloatTriDiagMatrix represents a tridiagonal matrix of single-precision floating point values. A tridiagonal matrix is a matrix which has all its non-zero entries on the main diagonal, the super diagonal, and the subdiagonal.
Public classFloatUpperTriMatrix
Class FloatUpperTriMatrix represents an upper triangular matrix of single-precision floating point values. An upper triangular matrix is a square matrix with all elements below the main diagonal equal to zero.
Public classFloatVector
Class FloatVector represents a mathematical vector of floating point numbers.
Public classCode exampleFloatWavelet
This class represents a single precision wavelet. There are fives types of built in wavelets avaiable: Harr, Daubechies, Least Asymmetric, Best Localized, and Coiflet. User generated wavelets can be created by provided the low-pass decimation filter parameters in the constructor.
Public classFZero
FZero finds a zero of the function in the given interval. Repeated roots are not found, FZero can find only bracketed single roots.
Public classGammaDistribution
Class GammaDistribution represents the gamma probability distribution.
Public classGaussKronrod21Integrator
Class GaussKronrod21Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 10-point and the Kronrod 21-point rule.
Public classGaussKronrod43Integrator
Class GaussKronrod43Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 21-point and the Kronrod 43-point rule.
Public classGaussKronrod87Integrator
Class GaussKronrod87Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 43-point and the Kronrod 87-point rule.
Public classGaussKronrodIntegrator
Class GaussKronrodIntegrator calculates an approximation of the integral of a function over a finite interval using Gauss-Kronrod rules.
Public classGeometricDistribution
Class GeometricDistribution represents the goemetric probability distribution.
Public classGlobalCurveFitAnova
Class GlobalCurveFitAnova computes ANOVA style statistics for the least squares model fit that result from a global curve fit. Available statistics include the residual standard error, the coefficient of determination (R2 and "adjusted" R2), the F-statistic and p-value for the overall model, and degrees of freedom.
Public classGlobalCurveFitter
Global fitting in involves fitting multiple datasets with the same fitting function. Parameters in the fitting function can optionally be shared amongst all datasets. If a parameter is shared, the fitting procedure will yield the same value for that parameter for all datasets. If a parameter is not shared, the fitting procedure will yield a unique value for that parameter for each dataset.
Public classGlobalFitParameterInfo
Contains information about a parameter in a global curve fit: name, description, shared or not shared. Only the sharing information is required.
Public classGlobalFittedParameter
Class for providing fit statistics about a global fit parameter after the fit has been performed.
Public classGlobalFixedFitParameterInfo
Contains information about a parameter with fixed value(s) in a global curve fit: name, description, shared or not shared, and the fixed value(s). If the parameter is not shared, then its values may be fixed for specific datasets. In this case the fixed values must be specified in using an IDictionary parameter. For example if the dictionary contained entries { 1, 1.0 }, { 3, 1.2 } this would mean the parameter has a fixed value of 1.0 in second dataset (zero based indexing) and a fixed value of 1.2 in the fourth dataset. If the parameter info object is constructed with a dictionary of fixed values it is assumed to be non-shared. If it is constructed with a single fixed value it is assumed to be shared. If a GlobalFixedFitParameterInfo has multiple fixed values and its sharing property is set to ParameterSharing.Shared, The first entry in the dictionary will be taken as the shared fixed value.
Public classGoldenMinimizer
Class GoldenMinimizer performs a golden section search for a minimium of a function within an interval known to contain a minimum.
Public classGoodnessOfFit
Class GoodnessOfFit tests goodness of fit for least squares model-fitting classes, such as LinearRegression, PolynomialLeastSquares, and OneVariableFunctionFitter.
Public classGoodnessOfFitParameter
Class GoodnessOfFitParameter tests statistical hypotheses about estimated parameters in regression models.
Public classHistogram
Class Histogram constructs and maintains a histogram of input data. Input data is sorted into bins and a count is kept of how many data points fall into each bin.
Public classIActiveSetQPSolver
Class IActiveSetQPSolver is an interface for classes that solver convex quadratic programming (QP) problems. In particular, classes that implement this abstract class may be used in the Active Set Sequential Quadratic Programming solver for general linear programming problems.
Public classIndependentRandomStreams
Base class for creating streams of independent random numbers. Deriving classes must construct the streams_ array.
Public classIndexArray
Class IndexArray presents 0-based indexices to the user, but uses 1-based indices internally.
Public classIndexOutOfRangeException
Exception thrown when an out of range index is passed to an NMath function.
Public classInputVariableCorrelator
Instances of the InputVariableCorrelator class are used to induce a desired rank correlation among input variables.
Public classInteriorPointQPSolver
Class for sovling quadratic programming (QP) problems using an interior point algorithm.
Public classInteriorPointQPSolverParams
Parameters controlling the behavior of the interior point quadratic programming algorithm in the InteriorPointQPSolver class.
Public classInterval
Class Interval represents a numeric interval with inclusive or exclusive lower and upper bounds.
Public classIntRandomBernoulliDistribution
Class IntRandomBernoulliDistribution generates random numbers from a discrete binomial distribution.
Public classIntRandomBinomialDistribution
Class IntRandomBinomialDistribution generates random numbers from a discrete binomial distribution.
Public classIntRandomGeometricDistribution
Class IntRandomGeometricDistribution generates random numbers from a discrete geometric distribution.
Public classIntRandomHypergeometricDistribution
Class IntRandomHypergeometricDistribution generates random numbers from a discrete hypergeometric distribution.
Public classIntRandomNegativeBinomialDistribution
Class IntRandomNegativeBinomialDistribution generates random numbers from a discrete negative binomial distribution.
Public classIntRandomPoissonDistribution
Class IntRandomPoissonDistribution generates random numbers from a discrete Poisson distribution.
Public classIntRandomPoissonVaryingMeanDistribution
Class IntRandomPoissonVaryingMeanDistribution generates random numbers from a discrete Poisson distribution with varying mean.
Public classIntRandomUniformBitsDistribution
Class IntRandomUniformBitsDistribution generates integer values with uniform bit distribution.
Public classIntRandomUniformDistribution
Class IntRandomUniformDistribution generates random numbers uniformly distributed over an interval.
Public classInvalidArgumentException
Exception thrown when an invalid argument is passed to an NMath function.
Public classInvalidBinBdryException
Exception thrown when a histogram operation results in invalid bin boundaries.
Public classIPLS1Calc
Interface for performing a Partial Least Squares (PLS) calculation.
Public classIPLS2Calc
Interface for performing a Partial Least Squares (PLS) calculation.
Public classJohnsonDistribution
Class JohnsonDistribution represents the Johnson system of distributions.
Public classKFoldsSubsets
Class KFoldsSubsets generates k-fold subsets for cross validation.
Public classCode exampleKMeansClustering
Class KMeansClustering performs k-means clustering on a set of data points.
Public classKruskalWallisTable
Class KruskalWallisTable summarizes the information of Kruskal-Wallis rank sum test.
Public classKruskalWallisTest
Class KruskalWallisTest performs a Kruskal-Wallis rank sum test.
Public classL1MeritStepSize
Class L1MeritStepSize computes the step size for a Sequential Quadratic Programming solver based on sufficient decrease in the L1 merit function.
Public classLagrangianFunction
Class LagrangianFunction represents the Lagrangian function associated with a nonlinear programming problem.
Public classLagrangianFunctionLagrangianGradientFunction
Class LagrangianGradientFunction derives from DoubleMultiVariableFunction for evaluating the gradient of the Lagrangian functions.
Public classLeapfrogRandomStreams
Class LeapfrogRandomStreams creates several independent streams of random numbers using the method know as leapfrogging.
Public classLeapfrogStream
Class LeapfrogStream represents a single leapfrog stream.
Public classLeaveOneOutSubsets
Class LeaveOneOutSubsets generates the index subsets for a leave-one-out cross validations calculation.
Public classLevenbergMarquardtMinimizer
Class for minimizing the L2 norm of a function using the Levenberg Marquardt algorithm.
Public classLikelihoodRatioStatistic
Class LikelihoodRatioStatistic computes the Likelihood Ratio Statistic values for a logistic regression.
Public classLinearAnnealingSchedule
Class LinearAnnealingSchedule encapsulates the linear descent of a starting temperature to zero. Each step has a specified number of iterations.
Public classLinearConstrainedProblem
Abstract class for representing an optimization problem with linear constraints.
Public classLinearConstraint
Class LinearConstraint represents a linear constraint for a constrained optimization problem.
Public classLinearProgrammingProblem
Class LinearProgrammingProblem encapsulates a Linear programming problem.
Public classLinearRegression
Class LinearRegression computes a multiple linear regression from an input matrix of independent variable values and vector of dependent variable values.
Public classLinearRegressionAnova
Class LinearRegressionAnova tests overall model significance for linear regressions computed by class LinearRegression.
Public classLinearRegressionParameter
Class LinearRegressionParameter tests statistical hypotheses about estimated parameters in linear regressions computed by class LinearRegression.
Public classLinearSpline
Class LinearSpline represents a function whose values are determined by linear interpolation between tabulated values.
Public classLinkage
Class Linkage provides functions for computing the distance between clusters of objects.
Public classLogisticDistribution
Class LogisticDistribution represents the logistic probability distribution with a specifed location (mean) and scale.
Public classLogisticRegressionParameterCalc
Class for performing a binomial logistic regression.
Public classLogisticRegressionAuxiliaryStatsParameterCalc
Class LogisticRegressionAuxiliaryStats computes pseudo R-squared metrics for a logistic regression, and odds ratios for the computed coefficients.
Public classLogisticRegressionFitAnalysisParameterCalc
Class for for calculating "goodness of fit" statistics for a logistic regression model.
Public classLogisticRegressionFitAnalysisParameterCalcHosmerLemeshowGroup
Class representing a group used in computing the Hosmer Lemeshow statistic for a logistic regression model.
Public classLogisticRegressionFitAnalysisParameterCalcHosmerLemeshowStatistic
Class containing the attributes of the Hosmer Lemeshow statistic for a logistic regression model.
Public classLogisticRegressionFitAnalysisParameterCalcPearsonChiSqrStatistic
Class containing the attributes of the Pearson chi-square statistic associated with a logistic regression model.
Public classLogisticRegressionFitAnalysisParameterCalcPearsonResidual
Class containing Pearson Residual attributes. The Pearson Residual is calculated for each covariate pattern.
Public classLogisticRegressionParameterParameterCalc
Class LogisticRegressionParameter tests statistical hypotheses about estimated parameters in linear regressions computed by class LogisticRegression.
Public classLognormalDistribution
Class LognormalDistribution represents the lognormal probability distribution.
Public classMatrixFunctions
Class MatrixFunctions provides standard mathematical functions for NMath Matrix structured sparse matrix types.
Public classMatrixNotSquareException
Exception thrown when a matrix operation requiring a square matrix is presented with a non-square one.
Public classMinimizerBase
Class MinimizerBase is the abstract base class for classes that perform function minimization.
Public classCode exampleMismatchedSizeException
Exception thrown when an operation is performed with operands whose sizes are incompatible with the operation.
Public classMixedIntegerLinearProgrammingProblem
Class MixedIntegerLinearProgrammingProblem encapsulates a Linear programming problem which may contain integral constraints.
Public classMixedIntegerNonlinearProgrammingProblem
Class MixedIntegerNonlinearProgrammingProblem represents a nonlinear programming problem.
Public classModifiedLevenbergMarquardtMinimizer
Class for minimizing the L2 norm of a function using the a modified Levenberg Marquardt algorithm.
Public classMovingWindowFilter
Class implementing data filtering by replacing data points f(i) with a linear combination of the data points immediately to the left and right of f(i). The user provides the coefficients to use in the linear combination. Static class methods are provided for generating coefficients to implement a moving average filter and a Savitzky-Golay smoothing filter.
Public classMultipleCurveFit
Class for performing simulatenous fitting of multiple data sets with shared fitting parameters. As an example suppose we have two sets of data points- dataset 1 = { (x11,y11), (x12,y12),...,(x1n,y1n) } dataset 2 = { (x21,y21), (x22,y22),...,(x2n,y2m) } And suppose we have two parameterized functions f1(beta,x) = cos(2*pi*beta(0)*x)*exp(-x/beta(1)) f2(beta,x) = beta(3) + beta(2)*exp(-(x/beta(1))) where beta is a vector of four parameters. The MultiCurveFit class solves the problem of finding the parameter values beta that best fit, in the least squares sense, the function f1 to dataset 1 and the function f2 to dataset 2 with the paramter beta(1) being the same for both datasets.
Public classMultipleCurveFitFunction
Function for simulatenous fitting of multiple data sets with shared fitting parameters. MultipleCurveFit
Public classMultipleCurveFitResidual
Calculates the residuals of a MultipleCurveFitFunction with a given set of parameters and data sets.
Public classMultipleFitCurveInfo
Class for pairing a parameterized function with a data set for use in performing a simulatenous fitting of multiple data sets with shared fitting parameters. MultipleCurveFit
Public classMultiVariableFunction Obsolete.
Class MultiVariableFunction represents multivariate functions.
Public classMultiVariableFunctionFitterM
Class MultiVariableFunctionFitter fits a generalized multivariable function to a set of points.
Protected classMultiVariableFunctionFitterMResidualFunction
Residual function. This is the function that is minimized to produce the parameters for the best fit.
Public classNaturalCubicSpline
Class NaturalCubicSpline represents a function determined by tabulated values. Function values are calculated using natural cubic spline interpolation.
Public classNegativeBinomialDistribution
Class NegativeBinomialDistribution represents the discrete probability distribution of obtaining N successes in a series of x trials, where the probability of success on each trial is P.
Public classNewtonRaphsonParameterCalc
Parameter calculation for a logistic regression model. The parameters are computed to maximize the log likelihood function for the model, using the Newton Raphson algorithm to compute the zeros of the first order partial derivaties of the log likelihood function.
Public classNewtonRaphsonRootFinder
Class NewtonRaphsonRootFinder finds roots of univariate functions using the Newton-Raphson algorithm.
Public classNiederreiterQuasiRandomGenerator
Class NiederreiterQuasiRandomGenerator is a quasi-random number generator which can be used for generating sequences of quasi-random point in n-dimensional space.
Public classNMathConfiguration
Class NMathConfiguration provides properties for controlling the loading of the NMath kernel assembly and native library, and specifying license keys.
Public classNMathException
Base class for exceptions thrown by the NMath product suite.
Public classCode exampleNMathFormatException
Exception thrown when a method encounters a faulty text representation.
Public classNMathFunctions
Class NMathFunctions provides standard mathematical functions for NMath types. Trigonometric functions, exponents, logarithms, powers, and square roots are provided for vector, matrix, and complex number types.
Public classNMathSettings
Class NMathSettings contains global settings for NMath classes.
Public classNMFact
Class NMFact performs non-negative matrix factorization.
Public classNMFAlsUpdate
Class NMFAlsUpdate encapsulates the Alternating Least Squares (ALS) update algorithm.
Public classNMFClusteringAlg
Class NMFClustering performs a Non-negative Matrix Factorization (NMF) of a given matrix.
Public classNMFConsensusMatrixAlg
Class NMFConsensusMatrix uses a non-negative matrix factorization to cluster samples.
Public classNMFDivergenceUpdate
Class NMFDivergenceUpdate encapulates an NMF update algorithm which minimizes a divergence functional.
Public classNMFGdClsUpdate
Class NMFGdClsUpdate encapsulates the Gradient Descent - Constrained Least Squares (GDCLS) algorithm for Nonnegative Matrix Facotorization (NMF).
Public classNMFMultiplicativeUpdate
Class NMFMultiplicativeUpdate encapsulates a multiplicative update algorithm for Nonnegative Matrix Factorization (NMF).
Public classNMFNonsmoothUpdate
Class NMFNonsmoothUpdate encapulates an NMF update algorithm which minimizes a cost functional designed to explicitly represent sparseness, in the form on nonsmoothness, which is controlled by a single parameter.
Public classNoncentralTDistribution
Class NoncentralTDistribution represents a generalized Student's t-distribution with the specified degrees of freedom and noncentrality parameter.
Public classNonlinearConstraint
Class NonlinearConstraint represents a nonlinear constraint in an optimization problem.
Public classNonlinearProgrammingProblem
Class NonlinearProgrammingProblem represents a nonlinear programming problem.
Public classNonModifiableElementException
Exception thrown when an attempt is made to change the value of an element in a structured matrix that cannot be changed.
Public classNormalDistribution
Class NormalDistribution represents the normal (Gaussian) probability distribution with a specifed mean and variance.
Public classNoRotation
Used as a class type parameter value to factor analysis classes when no factor rotation is desired.
Public classNumberOfFactors
The
NumberOfFactors
class contains static methods for creating function objects suitable for use as "number of factors" functors used in the factor extraction step of a factor analysis. These functions take as paramters the eigenvalues and eigenvectors values computed during factor extraction and return the number of factors to "keep".
Public classOdeSolverBase
Base class for ODE solvers which use a Runge-Kutta order 5 algorithm. Includes enums and functions for incorporating mass matrices into ODE's.
Protected classOdeSolverBaseConstMassMatrixOdeFcn
When solving ODE's of the form y' = M*f(t,y) where M is a constant "mass" matrix, this class provides a function g(t,y) for the right hand side of the above equation which incorporates the mass matrix M.
Protected classOdeSolverBaseMassMatrixOdeFcn
When solving ODE's of the form y' = M(t,y)*f(t,y) where M is a time-state dependent "mass" matrix, this class provides a function g(t,y) for the right hand side of the above equation which incorporates the mass matrix function M(t,y).
Public classOneSampleAndersonDarlingTest
Class OneSampleAndersonDarlingTest performs a Anderson-Darling test of the distribution of one sample.
Public classOneSampleKSTest
Class OneSampleKSTest performs a Kolmogorov-Smirnov test of the distribution of one sample.
Public classOneSampleTTest
Class OneSampleTTest compares a single sample mean to an expected mean from a normal distribution with an unknown standard deviation.
Public classOneSampleZTest
Class OneSampleZTest compares a single sample mean to an expected mean from a normal distribution with known standard deviation.
Public classOneVariableFunction
Class OneVariableFunction represents functions of one variable.
Public classOneVariableFunctionFitterM
Class OneVariableFunctionFitter fits a parameterized one variable function to a set of points.
Public classOneVariableFunctionFitterMCurveFitResidualFunction
Class representing the residual function for the curve fit.
Public classOneWayAnova
Class OneWayAnova computes and summarizes a traditional one-way (single factor) Analysis of Variance (ANOVA).
Public classOneWayAnovaTable
Class OneWayAnovaTable summarizes the information of a traditional one-way Analysis of Variance (ANOVA) table.
Public classOneWayRanova
Class OneWayRanova summarizes the information of a one-way repeated measures Analysis of Variance (RANOVA).
Public classOneWayRanovaTable
Class OneWayRanovaTable summarizes the information of a traditional one-way repeated measures Analysis of Variance (RANOVA) table.
Public classOpenClosedInterval
Class OpenClosedInterval represents a numeric interval with an exclusive lower bound and an inclusive upper bound.
Public classOpenInterval
Class OpenInterval represents a numeric interval with exclusive lower and upper bounds.
Public classOrderedConnectivityMatrix
Class OrderedConnectivityMatrix reorders the rows and columns of an connectivity matrix so that the most affiliated elements appear as clusters of higher values along the diagonal.
Public classParameterizedMultivariableFunction
Abstract class representing multi-variable a parameterized function.
Public classPCFactorExtraction
Class implementing the principle components (PC) algorithm for factor extraction when performing factor analysis. Used as a class type parameter for the factor analysis classes.
Public classPeakFinderBase
Abstract base class for all peak finding algorithms. The class is an enumerable collection of all found peaks.
Public classPeakFinderRuleBased
Class PeakFinderRuleBased simply returns all of the peaks subject to rules about peak height and peak separation. A peak is defined as a point which is higher that both neighbors or infinity. Non-infinity end points are excluded as a peak.
Public classCode examplePeakFinderSavitzkyGolay
Class PeakFinderSavitzkyGolay uses smooth Savitzky-Golay derivatives to find peaks in data and acts as a collection for the found peaks.
Public classPearsonsChiSquareTest
Class PearsonsChiSquareTest tests whether the frequency distribution of experimental outcomes are consistant with a particular theoretical distribution.
Public classPLS1
Class PLS1 performs a Partial Least Squares (PLS) regression calculation on a set of predictive and one-dimensional response values. The result is used to predict response variable values.
Public classPLS1Anova
Class PLS1Anova performs a standard ANalysis Of VAriance (ANOVA) for a Partial Least Squares 1 (PLS1) regression model.
Public classPLS1CrossValidation
Class PLS1CrossValidation performs an evaluation of a PLS (Partial Least Squares) model.
Public classPLS1CrossValidationData
Class PLS1CrossValidationData divides Partial Least Squares - one dimensional response variable,(PLS1), data into training and testing subsets.
Public classPLS1CrossValidationResult
Class PLS2CrossValidationResult performs a Partial Least Squares - one dimensional response variable, (PLS1), cross validation calculation.
Public classPLS1NipalsAlgorithm
Class PLS1NipalsAlgorithm encapsulates the Nonlinear Iterative PArtial Least Squares (NIPALS) algorithm for computing partial least squares regression components.
Public classPLS2
Class PLS2 performs a Partial Least Squares (PLS) regression calculation on a set of predictive and response values. The result is used to predict response variable values.
Public classPLS2Anova
Class PLS2Anova performs a standard ANalysis Of VAriance (ANOVA) for a Partial Least Squares (PLS) regression model.
Public classPLS2CrossValidation
Class PLS2CrossValidation performs an evaluation of a PLS (Partial Least Squares) model.
Public classPLS2CrossValidationData
Class PLS2CrossValidationData divides Partial Least Squares (PLS) data into training and testing subsets.
Public classPLS2CrossValidationResult
Class PLS2CrossValidationResult performs a Partial Least Squares (PLS) cross validation calculation.
Public classPLS2CrossValidationWithJackknife
Class PLS2CrossValidationWithJackknife performs an evaluation of a PLS (Partial Least Squares) model with model coefficient variance estimates and confidence intervals.
Public classPLS2NipalsAlgorithm
Class PLS2NipalsAlgorithm encapsulates the Nonlinear Iterative PArtial Least Squares (NIPALS) algorithm for computing partial least squares regression components.
Public classPLS2SimplsAlgorithm
Class PLS2SimplsAlgorithm encapsulates the Straightforward IMplementation of Partial Least Squares, or SIMPLS, algorithm (de Jong, 1993) for computing partial least squares regression components.
Public classPoissonDistribution
Class PoissonDistribution represents a poisson distribution with a specified lambda, which is both the mean and the variance of the distribution. The poisson distribution a discrete distribution representing the probability of obtaining exactly n successes in N trials.
Public classPolynomial
Class Polynomial represents a polynomial function as a vector of coefficients.
Public classPolynomialDifferentiator
Class PolynomialDifferentiator encapsulates exact differentiation of polynomials.
Public classPolynomialIntegrator
Class PolynomialIntegration encapsulates exact integration of polynomials.
Public classPolynomialLeastSquares
Class PolynomialLeastSquares performs a least squares fit of a polynomial to the data.
Public classPowellMinimizer
Class PowellMinimizer minimizes a multivariable function using Powell's Method.
Public classPowerMethod
Class for computing the dominant eigenvalue and eigenvector of a square matrix using the iterative power method.
Public classPrimalSimplexSolver Obsolete.
Class PrimalSimplexSolver is a class for solving linear programming prolems using the primal simplex method.
Public classPrimalSimplexSolverORTools
Class PrimalSimplexSolver is a class for solving linear programming prolems using the primal simplex method.
Public classPrimalSimplexSolverParams Obsolete.
Primal simplex algorithm parameters.
Public classProbabilityDistribution
Class ProbabilityDistribution is the abstract base class for classes that represent distributions of random variables.
Public classProcessCapability
Computes the process capability parameters Cp, Cpm, Cp for normally distributed data. If the data is not normal the Box-Cox transform can be used.
Public classProcessPerformance
Computes process performance parameters Pp and Ppk for normally distributed data. If the data is not normal the Box-Cox transform can be used.
Public classQRRegressionCalculation
Class QRRegressionCalculation computes linear regression parameters by the method of least squares using a QR decomposition.
Public classQuadraticProgrammingProblem
Class QuadraticProgrammingProblem encapsulates a quadratic programming (QP) problem.
Public classQuasiRandomNumberGenerator
Abstract base class for generating sequences of quasirandom points. A quasirandom sequence is a sequence of n-tuples that fills n-space more uniformly than uncorrelated random points.
Public classRandGenBeta
Class RandGenBeta generates random numbers from a beta distribution.
Public classRandGenBinomial
Class RandGenBinomial generates random numbers from a binomial distribution.
Public classRandGenExponential
Class RandGenExponential generates random numbers from an exponential distribution.
Public classRandGenGamma
Class RandGenGamma generates random numbers from an gamma distribution.
Public classRandGenGeometric
Class RandGenGeometric generaties random numbers from a Geometric distribution.
Public classRandGenJohnson
Class RandGenJohnson generates random numbers from a Johnson distribution.
Public classRandGenLogNormal
Class RandGenLogNormal generates random numbers from a lognormal distribution.
Public classRandGenMTwist
Class RandGenMTwist generates random numbers from a uniform distribution using the Mersenne Twister algorithm.
Public classRandGenNormal
Class RandGenNormal generates random numbers from a normal distribution.
Public classRandGenPareto
Class RandGenPareto generates random numbers from a Pareto distribution.
Public classRandGenPoisson
Class RandGenPoisson generates random numbers from an Poisson distribution.
Public classRandGenTriangular
Class RandGenTriangular generates random numbers from a triangular distribution.
Public classRandGenUniform
Class RandGenUniform generates random numbers from a uniform distribution.
Public classRandGenWeibull
Class RandGenWeibull generates random numbers from a Weibull distribution.
Public classRandomNumberGenerator
Abstract base class for NMath random number generators.
Public classRandomNumbersT, D
Class RandomNumbers is an adapter for the RandomNumberStream class to give the same behavior as a scalar-type random number generator.
Public classRandomNumberStream
Class RandomNumberStream is a vectorized random number generator which yields a stream of random numbers from various probability distributions.
Public classRange
Class Range represents a collection of indices that can be used to view a subset of data from another data structure. A Range is defined by a starting index, an ending index or enumerated Position value, and a step increment called the stride.
Public classReducedVarianceInputCorrelator
Instances of the ReducedVarianceInputCorrelator class are used to induce a desired rank correlation among input variables.
Public classRegressionBase
Base class for linear and logistic regression.
Public classRegressionFactorScores
Class implementing the
IFactorScores
interface for computing factor scores using the regression algorithm. The regression algorithm uses a least squares regression approach to predict factor scores. Specifically this method computes the solution X to the matrix equation RX = B, where R = covariance matrix, B = factor matrix, X = factor scores.
Public classRiddersDifferentiator
Class RidderDifferentiator encapsulates numerical differentiation of functions.
Public classRiddersRootFinder
Class RiddersRootFinder finds roots of univariate functions using Ridders' Method.
Public classRombergIntegrator
Class RombergIntegrator approximates integrals of functions over a given interval using the Romberg method.
Public classRootFinderBase
Abstract base class for classes that perform root finding on univariate functions.
Public classRungeKutta45OdeSolver
Class RungeKutta45OdeSolver solves an initial value, Ordinary Differential Equation (ODE) using an explicit Runge-Kutta (4,5) formula known as the Dormand-Prince pair.
Public classRungeKutta45OdeSolverOptions
User settable options for RungeKutta45OdeSolver.
Public classRungeKutta45OdeSolverSolutionYtype
Data structor contiaing solution values an statistics for an ODE solve.
Public classRungeKutta5OdeSolver
Class RungeKutta5OdeSolver solves an initial value, Ordinary Differential Equation (ODE) using a non-adaptive explicit Runge-Kutta formula of order 5.
Public classRungeKutta5OdeSolverOptions
User settable options for RungeKutta5OdeSolver.
Public classCode exampleSavitzkyGolay
Class generates the Savitzy-Golay filter coefficients for smoothing data or computing smoothed derivatives. Smoothed derivatives can be found up to the order of the fitting polynomial.
Public classCode exampleSavitzkyGolayFilter
Class SavitzkyGolayFilter is a correlation filter specialized for filtering with Savitzky-Golay coefficients with additional boundary options for better edge continuity. The default boundary option ShiftFilterCenter provides data smoothing all the way boundary ends.
Public classSecantRootFinder
Class SecantRootFinder finds roots of univariate functions using the secant method.
Public classSequentialQuadraticProgrammingSolver
Base class for sequential quadratic programming solvers.
Public classSequentialQuadraticProgrammingSolverIteration
Data structure containing various values for an iteration of a Sequential Quadratic Programming algorithm.
Public classShapiroWilkTest
Class ShapiroWilkTest tests the null hypothesis that the sample comes from a normally distributed population.
Public classSimplexSolverBase Obsolete.
Class SimplexSolverBase is an abstract base class for classes solving mixed integer linear programming prolems using variants of the simplex method.
Public classSimplexSolverBaseORTools
Class SimplexSolverBase is an abstract base class for classes solving mixed integer linear programming prolems using variants of the simplex method.
Public classSimplexSolverMixedIntParams Obsolete.
Class containing parameters for simplex based mixed integer linear programming solvers.
Public classSimplexSolverParamsBase Obsolete.
Base class for simplex solver paramters.
Public classSingularMatrixException
Exception thrown when a matrix operation requiring a non-singular matrix is presented with a singular one.
Public classSkipAheadRandomStreams
Class for creating several independent streams of random numbers using the method know as skip-ahead, or block-splitting.
Public classSkipAheadStream
Class SkipAheadStream represents a single skip-ahead stream.
Public classCode exampleSlice
Class Slice represents a collection of indices that can be used to view a subset of data from another data structure. A slice is defined by a starting index, a total number of elements, and a step increment called the stride.
Public classSmoothCubicSpline
Class SmoothCubicSpline calculates smoothing splines.
Public classSobolQuasiRandomGenerator
Class SobolQuasiRandomGenerator is quasi-random number generator which can be used for generating sequences of quasi-random point in n-dimensional space.
Public classSparseConstraintCoefficients
Class implementing the ILinearConstraintCoefficients for sparse linear constraint coefficients. Only the non-zero coefficients are stored.
Public classSparseMatrixBuilderT
Class SparseMatrixBuilder{T} serves as the base class for the sparse matrix builder classes of specific types. This class implements the interface System.Collections.Generic.IDictionary{IntPair,T}, providing matrix-like row/column indexing for setting and retrieving values. Only nonzero values are stored.
Public classSparseMatrixDataStorage, Type
Class SparseMatrixData stores general sparse matrix data.
Public classSparseMatrixFactT
Abstract base class for sparse matrix factorizations using the Parallel Direct Sparse Solver Interface (PARDISO).
Public classSparsePls
Class SparsePls performs a Partial Least Squares (PLS) calculation for the model X ~ Y with variable selection. The LASSO penalization is used on the pairs of loading vectors. SparsePls allows matrices with missing values in them by using the NIPALS algorithm to estimate them. Missing values are represented as Double.NaN.
Public classSparsePlsDa
Class for performing Discriminant Analysis (DA) using sparse Partial Least Squares (sPLS). This is a classical sPLS regression, but where the response variable is catagorical. The response vector Y is qualitative and is recoded as a dummy block matrix where each of the response categories are coded via an indicator variable. PLS-DA is then run as if Y was a continuous matrix.
Public classSparsePLSDACrossValidation
Class SparsePLSDACrossValidation performs an evaluation of a PLS (Partial Least Squares) model.
Public classSparseVectorDataT
Class SparseVectorData stores sparse vector data.
Public classSpecialFunctions
This class contains a collection of special functions.
Public classStatsFunctions
Class StatsFunctions provides statistical functions for NMath types, including descriptive statistics and special functions.
Public classStatsSettings
Class StatsSettings contains global settings for NMath Stats classes.
Public classStochasticHillClimbingParameters
Parameter class for the StochasticHillClimbingSolver class.
Public classStochasticHillClimbingSolver
Nonlinear programming solver that uses a stocastic hill climbing algorithm. It starts from a random set of decision values, and repeatedly tries small random changes to the decision values. It keeps changes that make the answer better, and rejects changes that make it worse.
Public classSubset
Class Subset represents a collection of indices that can be used to view a subset of data from another data structure.
Public classSVDRegressionCalculation
Class SVDRegressionCalculation computes linear regression parameters by the method of least squares using a singular value decomposition.
Public classTabulatedFunction
Class TabulatedFunction is an abstract class representing a function determined by tabulated values.
Public classTDistribution
Class TDistribution represents Student's t-distribution with the specified degrees of freedom.
Public classTriangularDistribution
Class TriangularDistribution represents the triangular probability distribution.
Public classTrustRegionMinimizer
Class TrustRegionMinimizer solves both constrained and unconstrained nonlinear least squares problems using the Trust Region method.
Public classTrustRegionParameterCalc
Parameter calculation for a logistic regression model. The parameters are computed to maximize the log likelihood function for the model, using a trust region optimization algorithm to compute the zeros of the first order partial derivaties of the log likelihood function. The minimization is performed by an instance of the class CenterSpace.NMath.Core.TrustRegionMinimizer and algorithms parameters may be controlled through this object. It is accessible through the Minimizer class property, and a TrustRegionParameterCalc instace may be constructed with a give TrustRegionMinimizer object which has the desired properties. TrustRegionMinimizer
Public classTwoSampleFTest
Class TwoSampleFTest tests if the variances of two populations are equal.
Public classTwoSampleKSTest
Class TwoSampleKSTest performs a two-sample Kolmogorov-Smirnov test to compare the distributions of values in two data sets.
Public classTwoSamplePairedTTest
Class TwoSamplePairedTTest tests if two paired sets of observed values differ from each other in a significant way.
Public classTwoSampleUnpairedTTest
Class TwoSampleUnpairedTTest tests the null hypothesis that the two population means corresponding to two random samples are equal.
Public classTwoSampleUnpairedUnequalTTest
Class TwoSampleUnpairedUnequalTTest tests the null hypothesis that the two population means corresponding to two random samples are equal.
Public classTwoVariableIntegrator
Class TwoVariableIntegrator integrates functions of two variables.
Public classTwoWayAnova
Class TwoWayAnova performs a balanced two-way analysis of variance.
Public classTwoWayAnovaBase
Base class for both balanced and unbalanced two way ANOVA.
Public classTwoWayAnovaTable
Class TwoWayAnovaTable summarizes the information of a traditional two-way Analysis of Variance (ANOVA) table.
Public classTwoWayAnovaTypeI
Class for performing a Type I ANOVA on unbalanced data. See the description of the base class TwoWayAnovaUnbalanced for a description of the notation. Type I, also called "sequential" sum of squares: SS(A) for factor A. SS(B | A) for factor B. SS(AB | B, A) for interaction AB. This tests the main effect of factor A, followed by the main effect of factor B after the main effect of A, followed by the interaction effect AB after the main effects.
Public classTwoWayAnovaTypeII
Class for performing a Type II ANOVA on unbalanced data. See the description of the base class TwoWayAnovaUnbalanced for a description of the notation. SS(A | B) for factor A. SS(B | A) for factor B. SS(AB | A, B) for interaction. This type tests for each main effect after the other main effect. Note that no significant interaction is assumed and you should look look at the test for interaction first (SS(AB | A, B)) and only if interaction after the main effects AB is not significant continue with the analysis for main effects.
Public classTwoWayAnovaTypeIII
Class for performing a Type III ANOVA on unbalanced data. See the description of the base class TwoWayAnovaUnbalanced for a description of the notation. SS(A | B, AB) for factor A. SS(B | A, AB) for factor B. SS(AB | A, B) for interaction. This type tests for the presence of a main effect after the other main effect and interaction. This approach is therefore valid in the presence of significant interactions. However, it is often not interesting to interpret a main effect if interactions are present (generally speaking, if a significant interaction is present, the main effects should not be further analysed).
Public classTwoWayAnovaUnbalanced
Class TwoWayAnovaUnbalanced is the base class for performing a two way ANOVA when the number of observations in each cell is not the same (an unbalanced design). In this case the main and interaction effects are interdependent, and we must obtain the marginal sum of squares associated with each factor after all the other factors have already been included in the model (the marginal sum of squares for each variable equals the incremental sum of squares for that variable when it is entered into the equation last). In terms of a regression approach to ANOVA, the marginal sum of squares due to a factor is the sum of squares for the set of dummy variables associated with that factor when those dummy variables are entered into the model last, after all other dummy variables. Classes deriving from TwoWayAnovaUnbalanced provide the ordering of dummy regression variables and use the base class to compute the resulting regressions and sums of squares.
Public classTwoWayAnovaUnbalancedOrderedLinearRegression
Class containing the linear regression object computed from a particular ordering of factor and interaction parameters. Note that a factor parameter or interaction parameters may be absent depending on which type of sum of squares is being computed.
Public classTwoWayAnovaUnbalancedParameterSlices
As long as the dummy regression parameters are the same, we may use the same regression matrix to compute the various marginal sums of squares. Since the dummy variables for a given factor, or the interaction parameters, will always be contiguous columns in the regression matrix, their location can be specified with slices. The ParameterSlices class specifies the slices where factor A, factor B, and interaction dummy variables are located in the regression matrix. The following terminology is used throughout: Regression matrix - the matrix of regression parameters include the intercept parameter, which is expressed as a leading column of 1's in the matrix. Predictor matrix - The matrix of regression parameters excluding the intercept parameter. Thus regression parameters start at column 1 in the regression matrix and column 0 in the predictor matrix.
Public classTwoWayAnovaUnbalancedTable
Class TwoWayAnovaUnbalancedTable summarizes the information of a traditional two-way Analysis of Variance (ANOVA) table.
Public classTwoWayRanova
Class TwoWayRanova performs a balanced two-way analysis of variance with repeated measures on one factor.
Public classTwoWayRanovaTable
Class TwoWayRanovaTable summarizes the information of a traditional two-way Analysis of Variance (RANOVA) table.
Public classTwoWayRanovaTwo
Class TwoWayRanovaTwo performs a balanced two-way analysis of variance with repeated measures on both factors.
Public classTwoWayRanovaTwoTable
Class TwoWayRanovaTwoTable summarizes the information of a traditional two-way Analysis of Variance, with repeated measures on both factors, table,
Public classUniformDistribution
Class UniformDistribution represents the Uniform probability distribution.
Public classVariableBounds
Class specifying a variable ID, lower and upper bounds, and a tolerance used in testing bounds compliance.
Public classVariableMetricMinimizer
Class VariableMetricMinimizer uses the Broyden-Fletcher-Goldfarb-Shanno variable metric algorithm to minimize multivariable functions.
Public classVariableOrderOdeSolver
Solver for stiff and non-stiff ordinary differential equations. The algorithm uses higher order methods and smaller step size when the solution varies rapidly.
Public classVariableOrderOdeSolverOptions
Class containing available options for the VariableOrderOdeSolver.
Public classVariableOrderOdeSolverSolutionYtype
Data structor contianing solution values and statistics for an ODE solve.
Public classVarimaxRotation
Class for computing the varimax rotation of the factor from a factor analysis. Rotates the coordinates to maximize the sum of the variances of the squared loadings. Kaiser normalization is optionally performed, and the default stopping tolerance (1e-12) is used.
Public classWavelet
This abstract class represents a wavelet. There are fives types of built in wavelets avaiable: Harr, Daubechies, Least Asymmetric, Best Localized, and Coiflet.
Public classWeibullDistribution
Class WeibullDistribution represents the Weibull probability distribution.
Public classWeibullParameterFunction
Public classWeightedRegressionAnova
Class for performing an Analysis Of Variance on a weighted linear least squares fit.
Public classWilcoxonSignedRankTest
Class WilcoxonSignedRankTest tests if two paired sets of observed values differ from each other in a significant way.
Public classZBenchNormal
Computes the ZBench for normally distributed data, percent defective, and the parts per million defective.
Structures
  StructureDescription
Protected structureDiscreteWaveletTransformLevelT
Represents one level of a DWT decomposition.
Public structureDoubleComplex
The DoubleComplex struct represents a complex number, consisting of a real part and an imaginary part.
Public structureExtrema
Represents an imutable extrema of a function in two dimensions.
Public structureFloatComplex
The FloatComplex struct represents a complex number, consisting of a real part and an imaginary part.
Public structureIntPair
Class IntPair represents a pair of integers.
Interfaces
  InterfaceDescription
Public interfaceIArnoldiShiftInvertOperations
Eigenvalue Arnoldi solver shift invert operations.
Public interfaceIBoundedNonlinearLeastSqMinimizer
Interface for nonlinear least squares minimizer where the solution is constrained by upper and lower bounds.
Public interfaceICrossValidationSubsets
Interface for generating subsets of data to be used in a cross validation process.
Public interfaceIDFColumn
Interface for data frame column types.
Public interfaceIDifferentiator
Interface for classes that perform differentiation of a function at a point.
Public interfaceIDoubleComplexEnumerator
Classes that implement the IDoubleComplexEnumerator interface behave like regular IEnumerator implementations except that they return a DoubleComplex instead of an object. They avoid casting and are therefore much faster.
Public interfaceIDoubleEnumerator
Classes that implement the IDoubleEnumerator interface behave like regular IEnumerator implementations except that they return a double instead of an object. They avoid casting and are therefore much faster.
Public interfaceIDoubleLeastSqWeightingFunction
Interface for least squares weighting functions.
Public interfaceIFactorExtraction
Interface for factor extration algorithms used in factor analysis.
Public interfaceIFactorRotation
Interface for factor analysis factor rotation algorithms. Factors are rotated in order to maximize the relationship between the variables and some of the factors.
Public interfaceIFactorScores
Interface for factor score computation in a factor analysis.
Public interfaceIFloatComplexEnumerator
Classes that implement the IFloatComplexEnumerator interface behave like regular IEnumerator implementations except that they return a FloatComplex instead of an object. They avoid casting and are therefore much faster.
Public interfaceIFloatEnumerator
Classes that implement the IFloatEnumerator interface behave like regular IEnumerator implementations except that they return a float instead of an object. They avoid casting and are therefore much faster.
Public interfaceIIntegrator
Interface for classes that perform integration of a function over an interval.
Public interfaceILinearConstraintCoefficients
Interface for the coefficients for a linear constraint in a non-linear optimization problem. The interface is an abstraction of a vector of real numbers representing the coefficients of a linear constraint and thus defines the indexer property [int index]. This interface allows for both sparse and dense implementations.
Public interfaceILogisticRegressionCalc
Interface class for calculating the parameters of a logistic regression model.
Public interfaceIMultiVariableDMinimizer
Interface for classes that perform minimization of multivariate functions using derivative information.
Public interfaceIMultiVariableMinimizer
Interface for classes that perform minimization of multivariate functions.
Public interfaceINMFUpdateAlgorithm
Interface to be implemented by all Non-negative Matrix Factorization (NMF) update algorithms used by the NMFact class.
Public interfaceINonlinearLeastSqMinimizer
Interface for nonlinear least squares minimizer.
Public interfaceIOneVariableDMinimizer
Interface for classes that perform minimization of univariate functions using derivative information.
Public interfaceIOneVariableDRootFinder
Interface for classes that find roots of univariate functions using derivative information.
Public interfaceIOneVariableMinimizer
Interface for classes that perform minimization of univariate functions.
Public interfaceIOneVariableRootFinder
Interface for classes that find roots of univariate functions using only function evaluations.
Public interfaceIRandomNumberDistributionT
Interface for random number distributions.
Public interfaceIRandomVariableMoments
Interface implemented by probablility distributions.
Public interfaceIRegressionCalculation
Interface for classes used by class LinearRegression to calculate regression parameters.
Public interfaceISliceableT
Implement this interface to indicate support of range slicing in a vector.
Public interfaceISparseMatrixStorageT
Interface for general sparse matrix storage formats.
Public interfaceISpecialFunctions
Public interfaceSequentialQuadraticProgrammingSolverILagrangianHessianUpdater
Interface for classes which provide a method for obtaining the updated value of the Hessian of the Lagrangian based on the current iteration data for a Sequentail Quadratic Programming algorithm.
Public interfaceSequentialQuadraticProgrammingSolverIStepSizeCalculator
Computes a step size alphak for performing the update xk+1 = xk + alphak*pk, where pk is the step direction vector.
Delegates
  DelegateDescription
Public delegateDistanceFunction
Functor that takes two vectors and returns a measure of the distance (similarity) between them.
Public delegateDoubleIterativelyReweightedLeastSqToleranceMetFunction
Tolerance met function delegate.
Public delegateLinkageFunction
Functor that computes the linkage (similarity) between two groups.
Public delegateOrderedConnectivityMatrixElementDistance
Given an entry aij in the connectivity matrix A, this delegate must return the distance between the elements i and j to be used for performing the hierarchical cluster analysis.
Public delegateRandomNumberGeneratorUniformRandomNumber
Functor for generating uniform deviates between zero and one.
Enumerations
  EnumerationDescription
Public enumerationActiveSetLineSearchSQPTerminationStatus
Enum for possible algorithm termination reasons.
Public enumerationArnoldiSolveStatus
Result of eigenvalue problem solve attempt using implicitly restarted Arnoldi iteration.
Public enumerationBairstowRootFinderSolveResultStatus
Status values indicating why iteration was terminated.
Public enumerationBalanceOption
Enumeration for specifying balancing options in eigenvalue decompositions.
Public enumerationBiasType
Enumeration for specifying a biased or unbiased estimator.
Public enumerationConjugateTransposeOption
Enum specifying a particualr conjugate transpose option.
Public enumerationConstrainedOptimizerSolveResult
Enum whose value indicate the status of the solution.
Public enumerationConstrainedOptimizerORToolsSolveResult
Enum whose value indicate the status of the solution.
Public enumerationConstraintType
Enumeration for specifying constraint types possible for the Constraint class and other constrained optimization classes.>
Public enumerationControlLimits
Emum specifics types of control limits.
Public enumerationConvolutionBaseWindowing
Options for handling the various convolution/correlation result boundaries.
Public enumerationConvolutionMode
Controls internal funtion of convolution class.
Public enumerationCorrelationBaseWindowing
Options for handling the various convolution/correlation result boundaries.
Public enumerationCorrelationMode
Public enumerationDiscreteDataIntegratorStrategy
Discrete data integration strategies.
Public enumerationDiscreteWaveletTransformThresholdMethod
Details thresholding methods.
Public enumerationDiscreteWaveletTransformThresholdPolicy
Thresholding policy to apply to details thresholding.
Public enumerationDiscreteWaveletTransformWaveletCoefficientType
The two types of wavelet coefficients.
Public enumerationDiscreteWaveletTransformWaveletMode
Method for padding the signal edges for improved DWT accuracy near signal edges.
Public enumerationDoubleRandomBetaDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomExponentialDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomGammaDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomGaussianDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomLogNormalDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomRayleighDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomUniformDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDoubleRandomWeibullDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationDualSimplexCosting Obsolete.
Possible values for the dual simplex solver costing parameter. These values specify the pivoting strategy used by the solver.
Public enumerationFFTDirection
Direction of FFT. Used for building FFTConfiguration types.
Public enumerationFFTDomain
Forward Domain of FFT. Used for building FFTConfiguration types.
Public enumerationFFTPrecision
Precision of FFT transform. Used for building FFTConfiguration types.
Public enumerationFloatRandomBetaDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomExponentialDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomGammaDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomGaussianDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomLogNormalDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomRayleighDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomUniformDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationFloatRandomWeibullDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationHypothesisType
Enumeration for specifying the form of an alternative hypothesis in a hypothesis test.
Public enumerationIActiveSetQPSolverAlgorithmStatus
Enum whose value indicate the status of the solution.
Public enumerationInteriorPointQPSolverParamsKktFormOption
KKT form options for the interior point quadratic programming solver.
Public enumerationInteriorPointQPSolverParamsPresolveLevelOption
Presolve options for the interior point quadratic programming solver.
Public enumerationInteriorPointQPSolverParamsSymbolicOrderingOption
Options for symbolic ordering for the interior point quadratic programming solver.
Public enumerationIntervalType
An enumeration representing the possible interval types classified according to whether or not the endpoints are included in the interval.
Public enumerationIntRandomPoissonDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationIntRandomUniformDistributionGenerationMethod
Enumeration specifying different methods of random number generation.
Public enumerationJohnsonTransformationType
Enumeration for specifying the type of transformation of a normal random variate in the Johnson system.
Public enumerationKMeansClusteringStart
An enumeration representing methods used to choose the initial cluster centers.
Public enumerationMovingWindowFilterBoundaryOption
Options for handling the boundaries in a moving window filter.
Public enumerationNonnegLeastSqTermination
Enumeration of possible nonnegative least squares algorithm termination states.
Public enumerationNormType
Enumeration for specifying different types of norms.
Public enumerationOdeSolverBaseOutputFunctionFlag
Output functions are functions supplied by the user to derived ODE solvers. These functions are called by solver during 1. Initialization. Before the first integration step is performed. 2. After each integration step. 3. When the solver is complete. Output functions are called with an OutputFunctionFlag parameter indicating under which of the above conditions it is being invoked.
Public enumerationParameterSharing
Enum for indicating whether a parameter is shared or not in a global curve fit calculation.
Public enumerationPeakFinderBasePeakSortOrder
Enumeration for specifying sorting order.
Public enumerationPeakFinderRuleBasedRules
Rules to filter peaks.
Public enumerationPosition
Enumeration for specifying different view positions of underlying data.
Public enumerationPrimalSimplexCosting
Costing algorithms supported by the primal simplex algorithm.
Public enumerationProductTransposeOption
Enum for specifying transpose operations to be performed on the operands of a matrix-matrix multiply operation.
Public enumerationRandomNumberStreamBasicRandGenType
Enumeration for the various algorithms available for generating random numbers uniformly dstributed in the interval [0, 1]
Public enumerationRandomNumberStreamStreamStatus
Enum indicating the status of a random number stream.
Public enumerationSavitzkyGolayFilterSavitzyGolayBoundaryOptions
Enumeration specifying Savitsky-Golay boundary options.
Public enumerationSimplexSolverMixedIntParamsBranchingStrategies
Enumeration of branching strategies used in the branch-and-bound algorithm.
Public enumerationSimplexSolverMixedIntParamsSearchStrategies
Enumeration of options for search strategies for the mixed integer linear programming solver.
Public enumerationSortingType
Enumeration for specifying different sorting types, such as ascending or descending order.
Public enumerationSparseMatrixFactTError
Enumeration for specifying possible return values for errors.
Protected enumerationSparseMatrixFactTMatrixType
Enumeration for specifying the types of matrices that can be factored.
Public enumerationSparsePLSMode
Partial Least Squares Mode.
Public enumerationStorageType
Enumeration for specifying the storage scheme of a matrix.
Public enumerationTrustRegionMinimizerCriterion
Enumeration for specifying the stop criterion.
Public enumerationTwoWayAnovaUnbalancedParameterOrder
Enumeration indicating the factors and their order in a sum of squares computation.
Public enumerationWaveletWavelets
Built-in wavelets organized by short name. The first letter abbreviates the wavelet family name, and number that follows, the wavelet length.