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#Com.numericalmethod.suanshu.analysis.function Classes and Interfaces - 79 results found.
| Name | Description | Type | Package | Framework |
| AbstractBivariateRealFunction | A bivariate real function takes two real arguments and outputs one real value. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| AbstractR1RnFunction | This is a function that takes one real argument and outputs one vector value. | Class | com.numericalmethod.suanshu.analysis.function.rn2rm | SuanShu |
| AbstractRealScalarFunction | This abstract implementation implements Function. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| AbstractRealVectorFunction | This abstract implementation implements Function. | Class | com.numericalmethod.suanshu.analysis.function.rn2rm | SuanShu |
| AbstractTrivariateRealFunction | A trivariate real function takes three real arguments and outputs one real value. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| AbstractUnivariateRealFunction | A univariate real function takes one real argument and outputs one real value. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |
| Beta | The beta function defined as: B(x,y) = frac{Gamma(x)Gamma(y)}{Gamma(x+y)}= int_0^1t^{x-1}(1-t)^{y-1},dt, x > 0, y > 0 | Class | com.numericalmethod.suanshu.analysis.function.special.beta | SuanShu |
| BetaRegularized | The Regularized Incomplete Beta function is defined as: I_x(p,q) = frac{B(x;,p,q)}{B(p,q)} = frac{1}{B(p,q)} int_0^x t^{p-1},(1-t)^{q-1},dt, p > 0, q > 0 | Class | com.numericalmethod.suanshu.analysis.function.special.beta | SuanShu |
| BetaRegularizedInverse | The inverse of the Regularized Incomplete Beta function is defined at: x = I^{-1}_{(p,q)}(u), 0 le u le 1 | Class | com.numericalmethod.suanshu.analysis.function.special.beta | SuanShu |
| BivariateRealFunction | A bivariate real function takes two real arguments and outputs one real value. | Interface | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| CauchyPolynomial | The Cauchy's polynomial of a polynomial takes this form: C(x) = | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| ContinuedFraction | A continued fraction representation of a number has this form: z = b_0 + cfrac{a_1}{b_1 + cfrac{a_2}{b_2 + cfrac{a_3}{b_3 + cfrac{a_4}{b_4 + ddots,}}}} | Class | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |
| ContinuedFraction .MaxIterationsExceededException | RuntimeException thrown when the continued fraction fails to converge for a given epsilon before a certain number of iterations. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |
| ContinuedFraction .Partials | This interface defines a continued fraction in terms of the partial numerators an, and the partial denominators bn. | Interface | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |
| CubicRoot | This is a cubic equation solver. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| CumulativeNormalHastings | Hastings algorithm is faster but less accurate way to compute the cumulative standard Normal. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| CumulativeNormalInverse | The inverse of the cumulative standard Normal distribution function is defined as: This implementation uses the Beasley-Springer-Moro algorithm. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| CumulativeNormalMarsaglia | Marsaglia is about 3 times slower but is more accurate to compute the cumulative standard Normal. | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Digamma | The digamma function is defined as the logarithmic derivative of the gamma function. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| DuplicatedAbscissae | This exception is thrown when a function has two same x-abscissae, hence ill-defined. | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu |
| Erf | The Error function is defined as: operatorname{erf}(x) = frac{2}{sqrt{pi}}int_{0}^x e^{-t^2} dt | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Erfc | This complementary Error function is defined as: operatorname{erfc}(x) | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| ErfInverse | The inverse of the Error function is defined as: operatorname{erf}^{-1}(x) | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| Function | The mathematical concept of a function expresses the idea that one quantity (the argument of the function, also known as the input) completely determines another quantity (the value, or output). | Interface | com.numericalmethod.suanshu.analysis.function | SuanShu |
| Function .EvaluationException | This is the RuntimeException thrown when it fails to evaluate an expression. | Class | com.numericalmethod.suanshu.analysis.function | SuanShu |
| FunctionOps | These are some commonly used mathematical functions. | Class | com.numericalmethod.suanshu.analysis.function | SuanShu |
| Gamma | The Gamma function is an extension of the factorial function to real and complex numbers, with its argument shifted down by 1. | Interface | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaGergoNemes | The Gergo Nemes' algorithm is very simple and quick to compute the Gamma function, if accuracy is not critical. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaLanczos | Lanczos approximation provides a way to compute the Gamma function such that the accuracy can be made arbitrarily precise. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaLanczosQuick | Lanczos approximation, computations are done in double. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaLowerIncomplete | The Lower Incomplete Gamma function is defined as: gamma(s,x) = int_0^x t^{s-1},e^{-t},{ m d}t = P(s,x)Gamma(s) | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaRegularizedP | The Regularized Incomplete Gamma P function is defined as: P(s,x) = frac{gamma(s,x)}{Gamma(s)} = 1 - Q(s,x), s geq 0, x geq 0 | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaRegularizedPInverse | The inverse of the Regularized Incomplete Gamma P function is defined as: x = P^{-1}(s,u), 0 geq u geq 1 | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaRegularizedQ | The Regularized Incomplete Gamma Q function is defined as: Q(s,x)=frac{Gamma(s,x)}{Gamma(s)}=1-P(s,x), s geq 0, x geq 0 | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| GammaUpperIncomplete | The Upper Incomplete Gamma function is defined as: Gamma(s,x) = int_x^{infty} t^{s-1},e^{-t},{ m d}t = Q(s,x) imes Gamma(s) | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| Gaussian | The Gaussian function is defined as: f(x) = a e^{- { frac{(x-b)^2 }{ 2 c^2} } } | Class | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| HornerScheme | Horner scheme is an algorithm for the efficient evaluation of polynomials in monomial form. | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| JenkinsTraubReal | The Jenkins-Traub algorithm is a fast globally convergent iterative method for solving for polynomial roots. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root.jenkinstraub | SuanShu |
| Lanczos | The Lanczos approximation is a method for computing the Gamma function numerically, published by Cornelius Lanczos in 1964. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| LinearRoot | This is a solver for finding the roots of a linear equation. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| LogBeta | This class represents the log of Beta function log(B(x, y)). | Class | com.numericalmethod.suanshu.analysis.function.special.beta | SuanShu |
| LogGamma | The log-Gamma function, (log (Gamma(z))), for positive real numbers, is the log of the Gamma function. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| LogGamma .Method | the available methods to compute (log (Gamma(z)))Lanczos approximation. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| MultinomialBetaFunction | A multinomial Beta function is defined as: frac{prod_{i=1}^K Gamma(alpha_i)}{Gammaleft(sum_{i=1}^K | Class | com.numericalmethod.suanshu.analysis.function.special.beta | SuanShu |
| OrderedPairs | Cartesian products and binary relations (and hence the ubiquitous functions) are defined in termsSee Also:Wikipedia: Ordered pair | Interface | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu |
| Pair | An ordered pair (x,y) is a pair of mathematical objects. | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu |
| PairComparatorByAbscissaFirst | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu | |
| PairComparatorByAbscissaOnly | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu | |
| PartialFunction | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu | |
| Polynomial | A polynomial is a UnivariateRealFunction that represents a finite length expression constructed from variables and constants, using the operations of addition, subtraction, multiplication, and constant non-negative whole number exponents. | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| PolyRoot | This is a solver for finding the roots of a polynomial equation. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| PolyRootSolver | A root (or a zero) of a polynomial p is a member x in the domain of p such that p(x) vanishes. | Interface | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| QuadraticFunction | A quadratic function takes this form: (f(x) = frac{1}{2} imes x'Hx + x'p + c). | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| QuadraticMonomial | A quadratic monomial has this form: x2 + ux + v. | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| QuadraticRoot | This is a solver for finding the roots of a quadratic equation, (ax^2 + bx + c = 0). | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| QuadraticSyntheticDivision | Divide a polynomial P(x) by a quadratic monomial (x2 + ux + v) to give the quotient Q(x) and the remainder (b * (x + u) + a). | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| QuarticRoot | This is a quartic equation solver that solves (ax^4 + bx^3 + cx^2 + dx + e = 0). | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| QuarticRoot .QuarticSolver | This defines a quartic equation solver. | Interface | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| QuarticRootFerrari | This is a quartic equation solver that solves (ax^4 + bx^3 + cx^2 + dx + e = 0) using the Ferrari method. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| QuarticRootFormula | This is a quartic equation solver that solves (ax^4 + bx^3 + cx^2 + dx + e = 0) using a root-finding formula. | Class | com.numericalmethod.suanshu.analysis.function.polynomial.root | SuanShu |
| R1Projection | Projection creates a real-valued function RealScalarFunction from a vector-valued function RealVectorFunction by taking only one of its coordinate components in the vector output. | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| R1toConstantMatrix | A constant matrix function maps a real number to a constant matrix: (R^n ightarrow A). | Class | com.numericalmethod.suanshu.analysis.function.matrix | SuanShu |
| R1toMatrix | This is a function that maps from R1 to a Matrix space. | Class | com.numericalmethod.suanshu.analysis.function.matrix | SuanShu |
| R2toMatrix | This is a function that maps from R2 to a Matrix space. | Class | com.numericalmethod.suanshu.analysis.function.matrix | SuanShu |
| Rastrigin | The Rastrigin function is a non-convex function used as a performance test problem for optimization algorithms. | Class | com.numericalmethod.suanshu.analysis.function.special | SuanShu |
| RealScalarFunction | A real valued function a (R^n ightarrow R) function, (y = f(x_1, . | Interface | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| RealScalarSubFunction | This constructs a RealScalarFunction from another RealScalarFunction by restricting/fixing the values of a subset of | Class | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| RealVectorFunction | A vector-valued function a (R^n ightarrow R^m) function, ([y_1,. | Interface | com.numericalmethod.suanshu.analysis.function.rn2rm | SuanShu |
| RealVectorSubFunction | This constructs a RealVectorFunction from another RealVectorFunction by restricting/fixing the values of a subset of variables. | Class | com.numericalmethod.suanshu.analysis.function.rn2rm | SuanShu |
| RntoMatrix | This interface is a function that maps from Rn to a Matrix space. | Interface | com.numericalmethod.suanshu.analysis.function.matrix | SuanShu |
| ScaledPolynomial | This constructs a scaled polynomial that has neither too big or too small coefficients, hence avoiding overflow or underflow. | Class | com.numericalmethod.suanshu.analysis.function.polynomial | SuanShu |
| SortedOrderedPairs | The ordered pairs are first sorted by abscissa, then by ordinate. | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu |
| StandardCumulativeNormal | The cumulative Normal distribution function describes the probability of a Normal random variable falling in the interval ((-infty, x]). | Interface | com.numericalmethod.suanshu.analysis.function.special.gaussian | SuanShu |
| StepFunction | A step function (or staircase function) is a finite linear combination of indicator functions of Informally speaking, a step function is a piecewise constant function having only finitely many | Class | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |
| SubFunction | A sub-function, g, is defined over a subset of the domain of another (original) function, | Class | com.numericalmethod.suanshu.analysis.function | SuanShu |
| Trigamma | The trigamma function is defined as the logarithmic derivative of the digamma function. | Class | com.numericalmethod.suanshu.analysis.function.special.gamma | SuanShu |
| Triple | A triple is a tuple of length three. | Class | com.numericalmethod.suanshu.analysis.function.tuple | SuanShu |
| TrivariateRealFunction | A trivariate real function takes three real arguments and outputs one real value. | Interface | com.numericalmethod.suanshu.analysis.function.rn2r1 | SuanShu |
| UnivariateRealFunction | A univariate real function takes one real argument and outputs one real value. | Interface | com.numericalmethod.suanshu.analysis.function.rn2r1.univariate | SuanShu |