Uses of Interface
dev.nm.analysis.function.rn2r1.RealScalarFunction
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Uses of RealScalarFunction in dev.nm.algebra.linear.vector.doubles.operation
Methods in dev.nm.algebra.linear.vector.doubles.operation with parameters of type RealScalarFunction Modifier and Type Method Description static VectorVectorFactory. foreachColumn(Matrix matrix, RealScalarFunction f)Constructs a vector in which each entry is the result of applying aRealScalarFunctionto each column of an input matrix.static VectorVectorFactory. foreachRow(Matrix matrix, RealScalarFunction f)Constructs a vector in which each entry is the result of applying aRealScalarFunctionto each row of an input matrix.static VectorVectorFactory. foreachVector(Vector[] vectors, RealScalarFunction f)Applies aRealScalarFunctionon each input vector.static VectorVectorFactory. foreachVector(Collection<Vector> vectors, RealScalarFunction f)Applies aRealScalarFunctionon each input vector. -
Uses of RealScalarFunction in dev.nm.analysis.curvefit.interpolation
Classes in dev.nm.analysis.curvefit.interpolation that implement RealScalarFunction Modifier and Type Class Description classLinearInterpolatorDefine a univariate function by linearly interpolating between adjacent points.classNevilleTableNeville's algorithm is a polynomial interpolation algorithm. -
Uses of RealScalarFunction in dev.nm.analysis.curvefit.interpolation.bivariate
Methods in dev.nm.analysis.curvefit.interpolation.bivariate that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionBicubicInterpolation. interpolate(BivariateGrid grid)RealScalarFunctionBicubicSpline. interpolate(BivariateGrid grid)RealScalarFunctionBilinearInterpolation. interpolate(BivariateGrid grid)RealScalarFunctionBivariateGridInterpolation. interpolate(BivariateGrid grid)Constructs a real valued function from a grid of observations. -
Uses of RealScalarFunction in dev.nm.analysis.curvefit.interpolation.multivariate
Methods in dev.nm.analysis.curvefit.interpolation.multivariate that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionMultivariateGridInterpolation. interpolate(MultivariateGrid grid)Construct a real valued function from a grid of observations.RealScalarFunctionRecursiveGridInterpolation. interpolate(MultivariateGrid grid) -
Uses of RealScalarFunction in dev.nm.analysis.differentialequation.ode.ivp.problem
Methods in dev.nm.analysis.differentialequation.ode.ivp.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionODE. F()Get the differential, \(y^{(n)} = F\).Constructors in dev.nm.analysis.differentialequation.ode.ivp.problem with parameters of type RealScalarFunction Constructor Description ODE(RealScalarFunction F, double[] initials, double x0, double x1)Construct an ODE of order n together with its initial values.ODE1stOrder(RealScalarFunction[] Y, double[] y0, double x0, double x1)Constructs a system of first order ODEs {Yi} with their initial values {yi0}. -
Uses of RealScalarFunction in dev.nm.analysis.differentiation
Classes in dev.nm.analysis.differentiation that implement RealScalarFunction Modifier and Type Class Description classRiddersRidders' method computes the numerical derivative of a function.Constructors in dev.nm.analysis.differentiation with parameters of type RealScalarFunction Constructor Description Ridders(RealScalarFunction f, int[] varidx)Construct the derivative function of a vector-valued function using Ridder's method.Ridders(RealScalarFunction f, int[] varidx, double rate, int discretization)Construct the derivative function of a vector-valued function using Ridder's method. -
Uses of RealScalarFunction in dev.nm.analysis.differentiation.multivariate
Classes in dev.nm.analysis.differentiation.multivariate that implement RealScalarFunction Modifier and Type Class Description classMultivariateFiniteDifferenceA partial derivative of a multivariate function is the derivative with respect to one of the variables with the others held constant.Constructors in dev.nm.analysis.differentiation.multivariate with parameters of type RealScalarFunction Constructor Description BorderedHessian(RealScalarFunction f, RealScalarFunction g, Vector x)Construct the bordered Hessian matrix for multivariate functions f and g at point x.Gradient(RealScalarFunction f, Vector x)Construct the gradient vector for a multivariate function f at point x.GradientFunction(RealScalarFunction f)Construct the gradient function of a real scalar function f.Hessian(RealScalarFunction f, Vector x)Construct the Hessian matrix for a multivariate function f at point x.HessianFunction(RealScalarFunction f)Construct the Hessian function of a real scalar function f.Jacobian(RealScalarFunction[] f, Vector x)Construct the Jacobian matrix for a multivariate function f at point x.MultivariateFiniteDifference(RealScalarFunction f, int[] varidx)Construct the partial derivative of a multi-variable function.Constructor parameters in dev.nm.analysis.differentiation.multivariate with type arguments of type RealScalarFunction Constructor Description Jacobian(List<RealScalarFunction> f, Vector x)Construct the Jacobian matrix for a multivariate function f at point x. -
Uses of RealScalarFunction in dev.nm.analysis.differentiation.univariate
Classes in dev.nm.analysis.differentiation.univariate that implement RealScalarFunction Modifier and Type Class Description classDBetaThis is the first order derivative function of theBetafunction w.r.t x, \({\partial \over \partial x} \mathrm{B}(x, y)\).classDBetaRegularizedThis is the first order derivative function of the Regularized Incomplete Beta function,BetaRegularized, w.r.t the upper limit, x.classDErfThis is the first order derivative function of the Error function,Erf.classDfdxThe first derivative is a measure of how a function changes as its input changes.classDGammaThis is the first order derivative function of the Gamma function, \({d \mathrm{\Gamma}(x) \over dx}\).classDGaussianThis is the first order derivative function of aGaussianfunction, \({d \mathrm{\phi}(x) \over dx}\).classDPolynomialThis is the first order derivative function of aPolynomial, which, again, is a polynomial.classFiniteDifferenceA finite difference (divided by a small increment) is an approximation of the derivative of a function. -
Uses of RealScalarFunction in dev.nm.analysis.function.polynomial
Classes in dev.nm.analysis.function.polynomial that implement RealScalarFunction Modifier and Type Class Description classCauchyPolynomialThe Cauchy's polynomial of a polynomial takes this form:classPolynomialA polynomial is aUnivariateRealFunctionthat represents a finite length expression constructed from variables and constants, using the operations of addition, subtraction, multiplication, and constant non-negative whole number exponents.classQuadraticMonomialA quadratic monomial has this form: x2 + ux + v.classScaledPolynomialThis constructs a scaled polynomial that has neither too big or too small coefficients, hence avoiding overflow or underflow. -
Uses of RealScalarFunction in dev.nm.analysis.function.rn2r1
Subinterfaces of RealScalarFunction in dev.nm.analysis.function.rn2r1 Modifier and Type Interface Description interfaceBivariateRealFunctionA bivariate real function takes two real arguments and outputs one real value.interfaceTrivariateRealFunctionA trivariate real function takes three real arguments and outputs one real value.Classes in dev.nm.analysis.function.rn2r1 that implement RealScalarFunction Modifier and Type Class Description classAbstractBivariateRealFunctionA bivariate real function takes two real arguments and outputs one real value.classAbstractRealScalarFunctionThis abstract implementation implementsFunction.dimensionOfRange()by always returning 1, andFunction.dimensionOfDomain()by returning the input argument for the dimension of domain.classAbstractTrivariateRealFunctionA trivariate real function takes three real arguments and outputs one real value.classQuadraticFunctionA quadratic function takes this form: \(f(x) = \frac{1}{2} \times x'Hx + x'p + c\).classR1ProjectionProjection creates a real-valued functionRealScalarFunctionfrom a vector-valued functionRealVectorFunctionby taking only one of its coordinate components in the vector output.classRealScalarSubFunctionThis constructs aRealScalarFunctionfrom anotherRealScalarFunctionby restricting/fixing the values of a subset of variables.Constructors in dev.nm.analysis.function.rn2r1 with parameters of type RealScalarFunction Constructor Description RealScalarSubFunction(RealScalarFunction f, Map<Integer,Double> fixing)Construct a scalar sub-function. -
Uses of RealScalarFunction in dev.nm.analysis.function.rn2r1.univariate
Subinterfaces of RealScalarFunction in dev.nm.analysis.function.rn2r1.univariate Modifier and Type Interface Description interfaceUnivariateRealFunctionA univariate real function takes one real argument and outputs one real value.Classes in dev.nm.analysis.function.rn2r1.univariate that implement RealScalarFunction Modifier and Type Class Description classAbstractUnivariateRealFunctionA univariate real function takes one real argument and outputs one real value.classContinuedFractionA continued fraction representation of a number has this form: \[ z = b_0 + \cfrac{a_1}{b_1 + \cfrac{a_2}{b_2 + \cfrac{a_3}{b_3 + \cfrac{a_4}{b_4 + \ddots\,}}}} \] ai and bi can be functions of x, which in turn makes z a function of x.classStepFunctionA step function (or staircase function) is a finite linear combination of indicator functions of intervals. -
Uses of RealScalarFunction in dev.nm.analysis.function.special
Classes in dev.nm.analysis.function.special that implement RealScalarFunction Modifier and Type Class Description classRastriginThe Rastrigin function is a non-convex function used as a performance test problem for optimization algorithms. -
Uses of RealScalarFunction in dev.nm.analysis.function.special.beta
Classes in dev.nm.analysis.function.special.beta that implement RealScalarFunction Modifier and Type Class Description classBetaThe beta function defined as: \[ B(x,y) = \frac{\Gamma(x)\Gamma(y)}{\Gamma(x+y)}= \int_0^1t^{x-1}(1-t)^{y-1}\,dt, x > 0, y > 0 \]classBetaRegularizedThe Regularized Incomplete Beta function is defined as: \[ I_x(p,q) = \frac{B(x;\,p,q)}{B(p,q)} = \frac{1}{B(p,q)} \int_0^x t^{p-1}\,(1-t)^{q-1}\,dt, p > 0, q > 0 \]classBetaRegularizedInverseThe inverse of the Regularized Incomplete Beta function is defined at: \[ x = I^{-1}_{(p,q)}(u), 0 \le u \le 1 \]classLogBetaThis class represents the log of Beta functionlog(B(x, y)).classMultinomialBetaFunctionA multinomial Beta function is defined as: \[ \frac{\prod_{i=1}^K \Gamma(\alpha_i)}{\Gamma\left(\sum_{i=1}^K \alpha_i\right)},\qquad\boldsymbol{\alpha}=(\alpha_1,\cdots,\alpha_K) \] -
Uses of RealScalarFunction in dev.nm.analysis.function.special.gamma
Classes in dev.nm.analysis.function.special.gamma that implement RealScalarFunction Modifier and Type Class Description classDigammaThe digamma function is defined as the logarithmic derivative of the gamma function.classGammaGergoNemesThe Gergo Nemes' algorithm is very simple and quick to compute the Gamma function, if accuracy is not critical.classGammaLanczosLanczos approximation provides a way to compute the Gamma function such that the accuracy can be made arbitrarily precise.classGammaLanczosQuickLanczos approximation, computations are done indouble.classGammaLowerIncompleteThe Lower Incomplete Gamma function is defined as: \[ \gamma(s,x) = \int_0^x t^{s-1}\,e^{-t}\,{\rm d}t = P(s,x)\Gamma(s) \] P(s,x) is the Regularized Incomplete Gamma P function.classGammaRegularizedPThe Regularized Incomplete Gamma P function is defined as: \[ P(s,x) = \frac{\gamma(s,x)}{\Gamma(s)} = 1 - Q(s,x), s \geq 0, x \geq 0 \]classGammaRegularizedPInverseThe inverse of the Regularized Incomplete Gamma P function is defined as: \[ x = P^{-1}(s,u), 0 \geq u \geq 1 \] Whens > 1, we use the asymptotic inversion method. Whens <= 1, we use an approximation of P(s,x) together with a higher-order Newton like method. In both cases, the estimated value is then improved using Halley's method, c.f.,HalleyRoot.classGammaRegularizedQThe Regularized Incomplete Gamma Q function is defined as: \[ Q(s,x)=\frac{\Gamma(s,x)}{\Gamma(s)}=1-P(s,x), s \geq 0, x \geq 0 \] The algorithm used for computing the regularized incomplete Gamma Q function depends on the values of s and x.classGammaUpperIncompleteThe Upper Incomplete Gamma function is defined as: \[ \Gamma(s,x) = \int_x^{\infty} t^{s-1}\,e^{-t}\,{\rm d}t = Q(s,x) \times \Gamma(s) \] The integrand has the same form as the Gamma function, but the lower limit of the integration is a variable.classLogGammaThe log-Gamma function, \(\log (\Gamma(z))\), for positive real numbers, is the log of the Gamma function.classTrigammaThe trigamma function is defined as the logarithmic derivative of the digamma function. -
Uses of RealScalarFunction in dev.nm.analysis.function.special.gaussian
Classes in dev.nm.analysis.function.special.gaussian that implement RealScalarFunction Modifier and Type Class Description classCumulativeNormalHastingsHastings algorithm is faster but less accurate way to compute the cumulative standard Normal.classCumulativeNormalInverseThe inverse of the cumulative standard Normal distribution function is defined as: \[ N^{-1}(u) /]classCumulativeNormalMarsagliaMarsaglia is about 3 times slower but is more accurate to compute the cumulative standard Normal.classErfThe Error function is defined as: \[ \operatorname{erf}(x) = \frac{2}{\sqrt{\pi}}\int_{0}^x e^{-t^2} dt \]classErfcThis complementary Error function is defined as: \[ \operatorname{erfc}(x) = 1-\operatorname{erf}(x) = \frac{2}{\sqrt{\pi}} \int_x^{\infty} e^{-t^2}\,dt \]classErfInverseThe inverse of the Error function is defined as: \[ \operatorname{erf}^{-1}(x) \]classGaussianThe Gaussian function is defined as: \[ f(x) = a e^{- { \frac{(x-b)^2 }{ 2 c^2} } } \] -
Uses of RealScalarFunction in dev.nm.analysis.root.multivariate
Methods in dev.nm.analysis.root.multivariate with parameters of type RealScalarFunction Modifier and Type Method Description VectorNewtonSystemRoot. solve(RealScalarFunction[] f, Vector guess)Searches for a root, x such that f(x) = 0. -
Uses of RealScalarFunction in dev.nm.misc.algorithm
Methods in dev.nm.misc.algorithm with parameters of type RealScalarFunction Modifier and Type Method Description double[]Bins. getBinKeyValues(RealScalarFunction f)Applies a function to the key of each bin. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.constraint
Methods in dev.nm.solver.multivariate.constrained.constraint that return types with arguments of type RealScalarFunction Modifier and Type Method Description List<RealScalarFunction>Constraints. getConstraints()Get the list of constraint functions. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.constraint.general
Methods in dev.nm.solver.multivariate.constrained.constraint.general that return types with arguments of type RealScalarFunction Modifier and Type Method Description List<RealScalarFunction>GeneralConstraints. getConstraints()Get the constraints.Constructors in dev.nm.solver.multivariate.constrained.constraint.general with parameters of type RealScalarFunction Constructor Description GeneralConstraints(RealScalarFunction... constraints)Construct an instance of constraints from an array of real-valued functions.GeneralEqualityConstraints(RealScalarFunction... constraints)Constructs an instance of equality constraints from an array of real-valued functions.GeneralGreaterThanConstraints(RealScalarFunction... constraints)Construct an instance of greater-than-or-equal-to inequality constraints from an array of real-valued functions.GeneralLessThanConstraints(RealScalarFunction... constraints)Construct an instance of less-than or equal-to inequality constraints from an array of real-valued functions.Constructor parameters in dev.nm.solver.multivariate.constrained.constraint.general with type arguments of type RealScalarFunction Constructor Description GeneralConstraints(Collection<RealScalarFunction> constraints)Construct an instance of constraints from a collection of real-valued functions.GeneralEqualityConstraints(Collection<RealScalarFunction> constraints)Constructs an instance of equality constraints from a collection of real-valued functions.GeneralGreaterThanConstraints(Collection<RealScalarFunction> constraints)Construct an instance of greater-than-or-equal-to inequality constraints from a collection of real-valued functions.GeneralLessThanConstraints(Collection<RealScalarFunction> constraints)Construct an instance of less-than or equal-to inequality constraints from a collection of real-valued functions. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.constraint.linear
Methods in dev.nm.solver.multivariate.constrained.constraint.linear that return types with arguments of type RealScalarFunction Modifier and Type Method Description List<RealScalarFunction>LinearConstraints. getConstraints()Constructors in dev.nm.solver.multivariate.constrained.constraint.linear with parameters of type RealScalarFunction Constructor Description LowerBoundConstraints(RealScalarFunction f, double lower)Construct a lower bound constraints for all variables in a function.NonNegativityConstraints(RealScalarFunction f)Construct a lower bound constraints for all variables in a function.UpperBoundConstraints(RealScalarFunction f, double lower)Construct an upper bound constraints for all variables in a function. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.problem
Methods in dev.nm.solver.multivariate.constrained.convex.sdp.problem that return types with arguments of type RealScalarFunction Modifier and Type Method Description List<RealScalarFunction>SDPDualProblem.EqualityConstraints. getConstraints() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.problem
Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionSOCPDualProblem. f()RealScalarFunctionSOCPDualProblem1. f()Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.problem that return types with arguments of type RealScalarFunction Modifier and Type Method Description List<RealScalarFunction>SOCPDualProblem.EqualityConstraints. getConstraints()List<RealScalarFunction>SOCPDualProblem1.EqualityConstraints. getConstraints() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.problem.portfoliooptimization
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.problem.portfoliooptimization that implement RealScalarFunction Modifier and Type Class Description classMarketImpact1Constructs the constraint coefficient arrays of a market impact term in the compact form.classPortfolioRiskExactSigmaConstructs the constraint coefficient arrays of the portfolio risk term in the compact form.classSOCPPortfolioConstraintAn SOCP constraint for portfolio optimization, e.g., market impact, is represented by a set of constraints in this form: \[ ||A^{T}x+c||_{2}\leq b^{T}x+d \] or this form: /[ A^T x = c, x \in \Re^m /] or this form: /[ A^T x \leq c, x \in \Re^m /]classSOCPPortfolioObjectiveFunctionConstructs the objective function for portfolio optimization.classSOCPRiskConstraint -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.problem
Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionLPProblemImpl1. f() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver
Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionLPRevisedSimplexSolver.Problem. f() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem that implement RealScalarFunction Modifier and Type Class Description classQPProblemOnlyEqualityConstraintsA quadratic programming problem with only equality constraints can be converted into a equivalent quadratic programming problem without constraints, hence a mere quadratic function. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.general.penaltymethod
Classes in dev.nm.solver.multivariate.constrained.general.penaltymethod that implement RealScalarFunction Modifier and Type Class Description classAbsoluteErrorPenaltyThis penalty function sums up the absolute error penalties.classCourantPenaltyThis penalty function sums up the squared error penalties.classFletcherPenaltyThis penalty function sums up the squared costs penalties.classMultiplierPenaltyA multiplier penalty function allows different weights to be assigned to the constraints.classPenaltyFunctionA function P: Rn -> R is a penalty function for a constrained optimization problem if it has these properties.classSumOfPenaltiesThis penalty function sums up the costs from a set of constituent penalty functions.classZeroPenaltyThis is a dummy zero cost (no cost) penalty function. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.general.sqp.activeset
Methods in dev.nm.solver.multivariate.constrained.general.sqp.activeset with parameters of type RealScalarFunction Modifier and Type Method Description SQPASVariationSQPActiveSetMinimizer.VariationFactory. newVariation(RealScalarFunction f, RealVectorFunction g, EqualityConstraints equal, GreaterThanConstraints greater)Construct a new instance ofSQPASVariationfor an SQP problem.voidSQPASVariation1. set(RealScalarFunction f, RealVectorFunction g, EqualityConstraints equal, GreaterThanConstraints greater)Associate this variation to a particular general constrained minimization problem.IterativeSolution<Vector>SQPActiveSetOnlyInequalityConstraintMinimizer. solve(RealScalarFunction f, RealVectorFunction g, GreaterThanConstraints greater)Minimize a function subject to only inequality constraints.IterativeSolution<Vector>SQPActiveSetOnlyInequalityConstraintMinimizer. solve(RealScalarFunction f, GreaterThanConstraints greater)Minimize a function subject to only inequality constraints.Constructors in dev.nm.solver.multivariate.constrained.general.sqp.activeset with parameters of type RealScalarFunction Constructor Description Solution(RealScalarFunction f, RealVectorFunction g, EqualityConstraints equal, GreaterThanConstraints greater) -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint
Fields in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint declared as RealScalarFunction Modifier and Type Field Description protected RealScalarFunctionSQPASEVariation1. fFields in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint with type parameters of type RealScalarFunction Modifier and Type Field Description protected List<RealScalarFunction>SQPASEVariation1. aMethods in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint with parameters of type RealScalarFunction Modifier and Type Method Description SQPASEVariationSQPActiveSetOnlyEqualityConstraint1Minimizer.VariationFactory. newVariation(RealScalarFunction f, EqualityConstraints equal)Construct a new instance ofSQPASEVariationfor an SQP problem.voidSQPASEVariation1. set(RealScalarFunction f, EqualityConstraints equal)Associate this variation to a particular general constrained minimization problem with only equality constraints.IterativeSolution<Vector>SQPActiveSetOnlyEqualityConstraint1Minimizer. solve(RealScalarFunction f, EqualityConstraints equal)Minimize a function subject to only equality constraints. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.integer
Methods in dev.nm.solver.multivariate.constrained.integer that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionIPProblemImpl1. f()Constructors in dev.nm.solver.multivariate.constrained.integer with parameters of type RealScalarFunction Constructor Description IPProblemImpl1(RealScalarFunction f, EqualityConstraints equal, LessThanConstraints less, int[] integers)Construct a constrained optimization problem with integral constraints.IPProblemImpl1(RealScalarFunction f, EqualityConstraints equal, LessThanConstraints less, int[] integers, double epsilon)Construct a constrained optimization problem with integral constraints. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.integer.bruteforce
Constructors in dev.nm.solver.multivariate.constrained.integer.bruteforce with parameters of type RealScalarFunction Constructor Description BruteForceIPProblem(RealScalarFunction f, EqualityConstraints equal, LessThanConstraints less, BruteForceIPProblem.IntegerDomain[] integers, double epsilon)Construct an integral constrained minimization problem with explicit integral domains.BruteForceIPProblem(RealScalarFunction f, BruteForceIPProblem.IntegerDomain[] integers, double epsilon)Construct an integral constrained minimization problem with explicit integral domains. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.integer.linear.bb
Methods in dev.nm.solver.multivariate.constrained.integer.linear.bb that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionILPNode. f() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.integer.linear.problem
Methods in dev.nm.solver.multivariate.constrained.integer.linear.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionILPProblemImpl1. f() -
Uses of RealScalarFunction in dev.nm.solver.multivariate.constrained.problem
Methods in dev.nm.solver.multivariate.constrained.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionBoxOptimProblem. f()RealScalarFunctionConstrainedOptimProblemImpl1. f()RealScalarFunctionNonNegativityConstraintOptimProblem. f()Constructors in dev.nm.solver.multivariate.constrained.problem with parameters of type RealScalarFunction Constructor Description BoxOptimProblem(RealScalarFunction f, Vector lower, Vector upper)Constructs an optimization problem with box constraints.BoxOptimProblem(RealScalarFunction f, BoxConstraints box)Constructs an optimization problem with box constraints.ConstrainedOptimProblemImpl1(RealScalarFunction f, EqualityConstraints equal, LessThanConstraints less)Constructs a constrained optimization problem.NonNegativityConstraintOptimProblem(RealScalarFunction f)Construct a constrained optimization problem with only non-negative variables. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim
Methods in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim with parameters of type RealScalarFunction Modifier and Type Method Description Best2Bin.DeBest2BinCellBest2Bin. getSimpleCell(RealScalarFunction f, Vector x)Rand1Bin.DeRand1BinCellRand1Bin. getSimpleCell(RealScalarFunction f, Vector x)Constructors in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim with parameters of type RealScalarFunction Constructor Description DeBest2BinCell(RealScalarFunction f, Vector x)DeOptimCell(RealScalarFunction f, Vector x)DeRand1BinCell(RealScalarFunction f, Vector x)Solution(RealScalarFunction f) -
Uses of RealScalarFunction in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim.constrained
Methods in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim.constrained with parameters of type RealScalarFunction Modifier and Type Method Description abstract ConstrainedCellFactory.ConstrainedCellConstrainedCellFactory. getSimpleCell(RealScalarFunction f, Vector x)Override this method to put in whatever constraints in the minimization problem.ConstrainedCellFactory.ConstrainedCellIntegralConstrainedCellFactory. getSimpleCell(RealScalarFunction f, Vector x)Constructors in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim.constrained with parameters of type RealScalarFunction Constructor Description ConstrainedCell(RealScalarFunction f, Vector x) -
Uses of RealScalarFunction in dev.nm.solver.multivariate.geneticalgorithm.minimizer.local
Methods in dev.nm.solver.multivariate.geneticalgorithm.minimizer.local with parameters of type RealScalarFunction Modifier and Type Method Description LocalSearchCellFactory.LocalSearchCellLocalSearchCellFactory. getSimpleCell(RealScalarFunction f, Vector x)Constructors in dev.nm.solver.multivariate.geneticalgorithm.minimizer.local with parameters of type RealScalarFunction Constructor Description LocalSearchCell(RealScalarFunction f, Vector x) -
Uses of RealScalarFunction in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid
Fields in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid declared as RealScalarFunction Modifier and Type Field Description protected RealScalarFunctionSimpleGridMinimizer.Solution. fMethods in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionRealScalarFunctionChromosome. f()Get the objective function.Methods in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid with parameters of type RealScalarFunction Modifier and Type Method Description SimpleCellFactory.SimpleCellSimpleCellFactory. getSimpleCell(RealScalarFunction f, Vector x)Construct an instance of aSimpleCell.Constructors in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid with parameters of type RealScalarFunction Constructor Description RealScalarFunctionChromosome(RealScalarFunction f, Vector x)Construct an instance ofRealScalarFunctionChromosome.SimpleCell(RealScalarFunction f, Vector x)Solution(RealScalarFunction f) -
Uses of RealScalarFunction in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid.firstgeneration
Constructors in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid.firstgeneration with parameters of type RealScalarFunction Constructor Description PerturbationAroundPoint(RealScalarFunction f, SimpleCellFactory factory, int poolSize, Vector var, Vector initial0, long seed)Generate an initial pool of chromosomes by adding a variance around a given initial.UniformMeshOverRegion(RealScalarFunction f, SimpleCellFactory factory, RandomLongGenerator uniform, int minDiscretization, Vector[] initials0, double epsilon)Generate an initial pool of chromosomes by putting a uniform mesh/grid/net over the entire region. -
Uses of RealScalarFunction in dev.nm.solver.multivariate.minmax
Methods in dev.nm.solver.multivariate.minmax that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionMinMaxProblem. error(T omega)e(x, ω) is the error function, or the minmax objective, for a given ω. -
Uses of RealScalarFunction in dev.nm.solver.problem
Methods in dev.nm.solver.problem that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionC2OptimProblemImpl. f()RealScalarFunctionOptimProblem. f()Get the objective function.Constructors in dev.nm.solver.problem with parameters of type RealScalarFunction Constructor Description C2OptimProblemImpl(RealScalarFunction f)Construct an optimization problem with an objective function.C2OptimProblemImpl(RealScalarFunction f, RealVectorFunction g)Construct an optimization problem with an objective function.C2OptimProblemImpl(RealScalarFunction f, RealVectorFunction g, RntoMatrix H)Construct an optimization problem with an objective function. -
Uses of RealScalarFunction in dev.nm.stat.distribution.multivariate.exponentialfamily
Constructors in dev.nm.stat.distribution.multivariate.exponentialfamily with parameters of type RealScalarFunction Constructor Description MultivariateExponentialFamily(RealScalarFunction h, RealVectorFunction eta, RealVectorFunction T, RealScalarFunction A)Construct a factory to construct probability distribution in the exponential family of this form. -
Uses of RealScalarFunction in dev.nm.stat.distribution.univariate.exponentialfamily
Constructors in dev.nm.stat.distribution.univariate.exponentialfamily with parameters of type RealScalarFunction Constructor Description ExponentialFamily(UnivariateRealFunction h, RealVectorFunction eta, AbstractR1RnFunction T, RealScalarFunction A)Construct a factory to construct probability distribution in the exponential family of this form. -
Uses of RealScalarFunction in dev.nm.stat.evt.evd.univariate.fitting
Methods in dev.nm.stat.evt.evd.univariate.fitting that return RealScalarFunction Modifier and Type Method Description RealScalarFunctionEstimateByLogLikelihood. getLogLikelihoodFunction()Get the log-likelihood function.Constructors in dev.nm.stat.evt.evd.univariate.fitting with parameters of type RealScalarFunction Constructor Description EstimateByLogLikelihood(Vector fittedParameters, RealScalarFunction logLikelihoodFunction) -
Uses of RealScalarFunction in dev.nm.stat.evt.evd.univariate.fitting.acer
Classes in dev.nm.stat.evt.evd.univariate.fitting.acer that implement RealScalarFunction Modifier and Type Class Description classACERFunctionThe ACER (Average Conditional Exceedance Rate) function \(\epsilon_k(\eta)\) approximates the probability \[ \epsilon_k(\eta) = Pr(X_k > \eta | X_1 \le \eta, X_2 \le \eta, ..., X_{k-1} \le \eta) \] for a sequence of stochastic process observations \(X_i\) with a k-step memory.classACERInverseFunctionThe inverse of the ACER function.classACERLogFunctionThe ACER function in log scale (base e), i.e., \(log(\epsilon_k(\eta))\).classACERReturnLevelGiven an ACER function, compute the return level \(\eta\) for a given return period \(R\). -
Uses of RealScalarFunction in dev.nm.stat.evt.function
Classes in dev.nm.stat.evt.function that implement RealScalarFunction Modifier and Type Class Description classReturnLevelGiven a GEV distribution of a random variable \(X\), the return level \(\eta\) is the value that is expected to be exceeded on average once every interval of time \(T\), with a probability of \(1 / T\).classReturnPeriodThe return period \(R\) of a level \(\eta\) for a random variable \(X\) is the mean number of trials that must be done for \(X\) to exceed \(\eta\). -
Uses of RealScalarFunction in dev.nm.stat.random.rng.multivariate.mcmc.hybrid
Methods in dev.nm.stat.random.rng.multivariate.mcmc.hybrid with parameters of type RealScalarFunction Modifier and Type Method Description static doubleAbstractHybridMCMC. H(LeapFrogging.DynamicsState state, RealScalarFunction logF, Vector m)Evaluates a system's total energy at a given state.Constructors in dev.nm.stat.random.rng.multivariate.mcmc.hybrid with parameters of type RealScalarFunction Constructor Description HybridMCMC(RealScalarFunction logF, RealVectorFunction dLogF, Vector m, double dt, int L, Vector initialState, RandomLongGenerator rlg)Constructs a new instance with the given parameters.MultipointHybridMCMC(RealScalarFunction logF, RealVectorFunction dLogF, Vector m, double dt, int L, int M, Vector w, Vector initialState, RandomLongGenerator uniform)Constructs a new instance with the given parameters.MultipointHybridMCMC(RealScalarFunction logF, RealVectorFunction dLogF, Vector m, double dt, int L, int M, Vector initialState, RandomLongGenerator uniform)Constructs a new instance with equal weights to the M configurations. -
Uses of RealScalarFunction in dev.nm.stat.random.rng.multivariate.mcmc.metropolis
Methods in dev.nm.stat.random.rng.multivariate.mcmc.metropolis with parameters of type RealScalarFunction Modifier and Type Method Description static booleanMetropolisUtils. isProposalAccepted(RealScalarFunction logf, RandomLongGenerator uniform, Vector currentState, Vector proposedState)Uses the given LOG density function to determine whether the given state transition should be accepted.static doubleMetropolisUtils. logAcceptanceRatio(RealScalarFunction logf, Vector currentState, Vector proposedState)Computes the log of the acceptance ratio.Constructors in dev.nm.stat.random.rng.multivariate.mcmc.metropolis with parameters of type RealScalarFunction Constructor Description Metropolis(RealScalarFunction logf, Vector initialState, double sigma, RandomLongGenerator uniform)Constructs a new instance, which draws the offset of the next proposed state from the previous state from a standard Normal distribution, with the given variance and zero covariance.Metropolis(RealScalarFunction logf, Vector initialState, Matrix scale, RandomLongGenerator uniform)Constructs a new instance, which draws the offset of the next proposed state from the previous state from a standard Normal distribution, multiplied by the given scale matrix.Metropolis(RealScalarFunction logf, RealVectorFunction proposalFunction, Vector initialState, RandomLongGenerator uniform)Constructs a new instance with the given parameters.MetropolisHastings(RealScalarFunction logf, ProposalFunction proposalFunction, MetropolisHastings.ProposalDensityFunction proposalDensity, Vector initialState, RandomNumberGenerator rng)Constructs a new instance with the given parameters.RobustAdaptiveMetropolis(RealScalarFunction logf, double targetAcceptance, Vector initialState, RandomLongGenerator uniform)Constructs an instance which assumes an initial variance of 1 per variable, uses a gamma of 0.5.RobustAdaptiveMetropolis(RealScalarFunction logf, Matrix initialScale, double gamma, double targetAcceptance, Vector initialState, RandomStandardNormalGenerator rnorm, RandomLongGenerator uniform)Constructs a new instance with the given parameters. -
Uses of RealScalarFunction in dev.nm.stat.regression.linear.logistic
Methods in dev.nm.stat.regression.linear.logistic that return RealScalarFunction Modifier and Type Method Description static RealScalarFunctionLogisticRegression. logLikelihood(LogisticProblem problem)Constructs the log-likelihood function for a logistic regression problem. -
Uses of RealScalarFunction in dev.nm.stat.stochasticprocess.univariate.filtration
Classes in dev.nm.stat.stochasticprocess.univariate.filtration that implement RealScalarFunction Modifier and Type Class Description classBtThis is aFiltrationFunctionthat returns \(B(t_i)\), the Brownian motion value at the i-th time point.classF_Sum_BtDtThis represents a function of this integral \[ I = \int_{0}^{1} B(t)dt \]classF_Sum_tBtDtThis represents a function of this integral \[ \int_{0}^{1} (t - 0.5) * B(t) dt \]classFiltrationFunctionA filtration function, parameterized by a fixed filtration, is a function of time, \(f(\mathfrak{F_{t_i}})\). -
Uses of RealScalarFunction in dev.nm.stat.timeseries.linear.univariate
Classes in dev.nm.stat.timeseries.linear.univariate that implement RealScalarFunction Modifier and Type Class Description classAutoCorrelationFunctionThis is the auto-correlation function of a univariate time series {xt}.classAutoCovarianceFunctionThis is the auto-covariance function of a univariate time series {xt}. -
Uses of RealScalarFunction in dev.nm.stat.timeseries.linear.univariate.sample
Classes in dev.nm.stat.timeseries.linear.univariate.sample that implement RealScalarFunction Modifier and Type Class Description classSampleAutoCorrelationThis is the sample Auto-Correlation Function (ACF) for a univariate data set.classSampleAutoCovarianceThis is the sample Auto-Covariance Function (ACVF) for a univariate data set.classSamplePartialAutoCorrelationThis is the sample partial Auto-Correlation Function (PACF) for a univariate data set. -
Uses of RealScalarFunction in dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma
Classes in dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma that implement RealScalarFunction Modifier and Type Class Description classAutoCorrelationCompute the Auto-Correlation Function (ACF) for an AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.classAutoCovarianceComputes the Auto-CoVariance Function (ACVF) for an AutoRegressive Moving Average (ARMA) model by recursion. -
Uses of RealScalarFunction in tech.nmfin.portfoliooptimization.lai2010.ceta
Classes in tech.nmfin.portfoliooptimization.lai2010.ceta that implement RealScalarFunction Modifier and Type Class Description classCetaThe function C(η) to be maximized (Eq. -
Uses of RealScalarFunction in tech.nmfin.portfoliooptimization.lai2010.ceta.maximizer
Classes in tech.nmfin.portfoliooptimization.lai2010.ceta.maximizer that implement RealScalarFunction Modifier and Type Class Description static classCetaMaximizer.NegCetaFunction -
Uses of RealScalarFunction in tech.nmfin.portfoliooptimization.socp.constraints
Classes in tech.nmfin.portfoliooptimization.socp.constraints that implement RealScalarFunction Modifier and Type Class Description classSOCPLinearBlackListA black list means that the positions of some assets must be zero.classSOCPLinearMaximumLoanA maximum loan constraint.classSOCPLinearSectorNeutralityA sector neutrality means that the sum of weights for given sectors are zero.classSOCPLinearSelfFinancingA self financing constraint.classSOCPLinearZeroValueA zero value constraint.classSOCPMaximumLoanTransforms a maximum loan constraint into the compact SOCP form.classSOCPNoTradingList1Transforms a black list (not to trade a new position) constraint into the compact SOCP form.classSOCPSectorNeutralityTransforms a sector neutral constraint into the compact SOCP form.classSOCPSelfFinancingTransforms a self financing constraint into the compact SOCP form.classSOCPZeroValueTransforms a zero value constraint into the compact SOCP form. -
Uses of RealScalarFunction in tech.nmfin.portfoliooptimization.socp.constraints.ybar
Classes in tech.nmfin.portfoliooptimization.socp.constraints.ybar that implement RealScalarFunction Modifier and Type Class Description classSOCPLinearSectorExposureA sector exposure constraint.classSOCPNoTradingList2Transforms a black list (not to trade a new position) constraint into the compact SOCP form.classSOCPSectorExposureTransforms a sector exposure constraint into the compact SOCP form.
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