Uses of Interface
dev.nm.analysis.function.matrix.RntoMatrix
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Uses of RntoMatrix in dev.nm.analysis.differentiation.differentiability
Methods in dev.nm.analysis.differentiation.differentiability that return RntoMatrix Modifier and Type Method Description RntoMatrixC2. H()Get the Hessian matrix function, H, of a real valued function f. -
Uses of RntoMatrix in dev.nm.analysis.differentiation.multivariate
Classes in dev.nm.analysis.differentiation.multivariate that implement RntoMatrix Modifier and Type Class Description classHessianFunctionThe Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x.classJacobianFunctionThe Jacobian function, J(x), evaluates the Jacobian of a real vector-valued function f at a point x. -
Uses of RntoMatrix in dev.nm.analysis.function.matrix
Classes in dev.nm.analysis.function.matrix that implement RntoMatrix Modifier and Type Class Description classR1toConstantMatrixA constant matrix function maps a real number to a constant matrix: \(R^n \rightarrow A\).classR1toMatrixThis is a function that maps from R1 to a Matrix space.classR2toMatrixThis is a function that maps from R2 to a Matrix space. -
Uses of RntoMatrix in dev.nm.solver.multivariate.unconstrained.c2.steepestdescent
Methods in dev.nm.solver.multivariate.unconstrained.c2.steepestdescent with parameters of type RntoMatrix Modifier and Type Method Description IterativeSolution<Vector>GaussNewtonMinimizer. solve(RealVectorFunction vf, RntoMatrix J)Solve the minimization problem to minimize F = vf' * vf.Constructors in dev.nm.solver.multivariate.unconstrained.c2.steepestdescent with parameters of type RntoMatrix Constructor Description GaussNewtonImpl(C2OptimProblem problem, RntoMatrix J) -
Uses of RntoMatrix in dev.nm.solver.problem
Methods in dev.nm.solver.problem that return RntoMatrix Modifier and Type Method Description RntoMatrixC2OptimProblemImpl. H()Constructors in dev.nm.solver.problem with parameters of type RntoMatrix Constructor Description C2OptimProblemImpl(RealScalarFunction f, RealVectorFunction g, RntoMatrix H)Construct an optimization problem with an objective function. -
Uses of RntoMatrix in dev.nm.stat.timeseries.linear.multivariate
Classes in dev.nm.stat.timeseries.linear.multivariate that implement RntoMatrix Modifier and Type Class Description classMultivariateAutoCorrelationFunctionThis is the auto-correlation function of a multi-dimensional time series {Xt}.classMultivariateAutoCovarianceFunctionThis is the auto-covariance function of a multi-dimensional time series {Xt}, \[ K(i, j) = E((X_i - \mu_i) \times (X_j - \mu_j)') \] For a stationary process, the auto-covariance depends only on the lag, |i - j|. -
Uses of RntoMatrix in dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma
Classes in dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma that implement RntoMatrix Modifier and Type Class Description classVARMAAutoCorrelationCompute the Auto-Correlation Function (ACF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.classVARMAAutoCovarianceCompute the Auto-CoVariance Function (ACVF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.
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