Uses of Interface
dev.nm.analysis.function.matrix.RntoMatrix
-
-
Uses of RntoMatrix in dev.nm.analysis.differentiation.differentiability
Methods in dev.nm.analysis.differentiation.differentiability that return RntoMatrix Modifier and Type Method Description RntoMatrix
C2. 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 class
HessianFunction
The Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x.class
JacobianFunction
The 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 class
R1toConstantMatrix
A constant matrix function maps a real number to a constant matrix: \(R^n \rightarrow A\).class
R1toMatrix
This is a function that maps from R1 to a Matrix space.class
R2toMatrix
This 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 RntoMatrix
C2OptimProblemImpl. 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 class
MultivariateAutoCorrelationFunction
This is the auto-correlation function of a multi-dimensional time series {Xt}.class
MultivariateAutoCovarianceFunction
This 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 class
VARMAAutoCorrelation
Compute the Auto-Correlation Function (ACF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.class
VARMAAutoCovariance
Compute the Auto-CoVariance Function (ACVF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that EXt = 0.
-