Uses of Class
dev.nm.algebra.linear.matrix.doubles.matrixtype.dense.triangle.SymmetricMatrix
-
-
Uses of SymmetricMatrix in dev.nm.algebra.linear.matrix.doubles.matrixtype
Subclasses of SymmetricMatrix in dev.nm.algebra.linear.matrix.doubles.matrixtype Modifier and Type Class Description class
HilbertMatrix
A Hilbert matrix, H, is a symmetric matrix with entries being the unit fractions H[i][j] = 1 / (i + j -1) -
Uses of SymmetricMatrix in dev.nm.algebra.linear.matrix.doubles.matrixtype.dense.triangle
Methods in dev.nm.algebra.linear.matrix.doubles.matrixtype.dense.triangle that return SymmetricMatrix Modifier and Type Method Description SymmetricMatrix
SymmetricMatrix. deepCopy()
SymmetricMatrix
SymmetricMatrix. ONE()
SymmetricMatrix
SymmetricMatrix. opposite()
SymmetricMatrix
SymmetricMatrix. scaled(double scalar)
SymmetricMatrix
SymmetricMatrix. t()
The transpose of a symmetric matrix is the same as itself.SymmetricMatrix
SymmetricMatrix. ZERO()
Constructors in dev.nm.algebra.linear.matrix.doubles.matrixtype.dense.triangle with parameters of type SymmetricMatrix Constructor Description SymmetricMatrix(SymmetricMatrix S)
Copy constructor. -
Uses of SymmetricMatrix in dev.nm.algebra.linear.matrix.doubles.operation
Methods in dev.nm.algebra.linear.matrix.doubles.operation that return SymmetricMatrix Modifier and Type Method Description static SymmetricMatrix
MatrixFactory. randomSymmetricMatrix(int dim, RandomNumberGenerator rng)
Constructs a random SymmetricMatrix. -
Uses of SymmetricMatrix in dev.nm.analysis.differentiation.multivariate
Subclasses of SymmetricMatrix in dev.nm.analysis.differentiation.multivariate Modifier and Type Class Description class
BorderedHessian
A bordered Hessian matrix consists of the Hessian of a multivariate function f, and the gradient of a multivariate function g.class
Hessian
The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function. -
Uses of SymmetricMatrix in dev.nm.solver.multivariate.constrained.convex.sdp.problem
Methods in dev.nm.solver.multivariate.constrained.convex.sdp.problem that return SymmetricMatrix Modifier and Type Method Description SymmetricMatrix
SDPDualProblem. A(int i)
Gets Ai.SymmetricMatrix
SDPPrimalProblem. A(int i)
Gets Ai.SymmetricMatrix
SDPDualProblem. C()
Gets C.SymmetricMatrix
SDPPrimalProblem. C()
Gets C.Constructors in dev.nm.solver.multivariate.constrained.convex.sdp.problem with parameters of type SymmetricMatrix Constructor Description EqualityConstraints(Vector b, SymmetricMatrix C, SymmetricMatrix[] A)
Construct the equality constraints for a dual SDP problem, \(\sum_{i=1}^{p}y_i\mathbf{A_i}+\textbf{S} = \textbf{C}, \textbf{S} \succeq \textbf{0}\).SDPDualProblem(Vector b, SymmetricMatrix C, SymmetricMatrix[] A)
Constructs a dual SDP problem.SDPPrimalProblem(SymmetricMatrix C, SymmetricMatrix[] A)
Constructs a primal SDP problem. -
Uses of SymmetricMatrix in tech.nmfin.meanreversion.daspremont2008
Methods in tech.nmfin.meanreversion.daspremont2008 that return SymmetricMatrix Modifier and Type Method Description SymmetricMatrix
CovarianceEstimation. covariance()
SymmetricMatrix
CovarianceEstimation. inverseCovariance()
Constructors in tech.nmfin.meanreversion.daspremont2008 with parameters of type SymmetricMatrix Constructor Description ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A, SymmetricMatrix B)
Constructs the problem described in Section 3.2, d'Aspremont (2008), changed to a minimization problem.ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A, SymmetricMatrix B, boolean isMinimizationProblem)
Constructs the problem described in Section 3.2, d'Aspremont (2008).ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A, SymmetricMatrix B, int maxIterations, double weightRank, double weightCardinality, double tol, boolean isMinimizationProblem)
Constructs the problem described in Section 3.2, d'Aspremont (2008).
-