| Modifier and Type | Method and Description |
|---|---|
RntoMatrix |
C2.H()
Get the Hessian matrix function, H, of a real valued function f.
|
| Modifier and Type | Class and 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.
|
| Modifier and Type | Class and 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 \(R^{1}\) to a Matrix space.
|
class |
R2toMatrix
This is a function that maps from \(R^{2}\) to a Matrix space.
|
| Modifier and Type | Method and Description |
|---|---|
IterativeSolution<Vector> |
GaussNewtonMinimizer.solve(RealVectorFunction vf,
RntoMatrix J)
Solve the minimization problem to minimize F = vf' * vf.
|
| Constructor and Description |
|---|
GaussNewtonImpl(C2OptimProblem problem,
RntoMatrix J) |
| Modifier and Type | Method and Description |
|---|---|
RntoMatrix |
C2OptimProblemImpl.H() |
| Constructor and Description |
|---|
C2OptimProblemImpl(RealScalarFunction f,
RealVectorFunction g,
RntoMatrix H)
Construct an optimization problem with an objective function.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MultivariateAutoCorrelationFunction
This is the auto-correlation function of a multi-dimensional time series {Xt}.
\[
Y_{i,j} = E((X_i - \mu_i) \times (X_j - \mu_j)')
\\
\rho(i, j) = \frac{Y_{i,j}}{\sqrt{Y_{i,i}Y_{j,j}}}
\]
For a stationary process, the auto-correlation depends only on the lag, |i - j|.
|
class |
MultivariateAutoCovarianceFunction
This is the auto-covariance function of a multi-dimensional time series \(\{X_{t}\}\),
\[
K(i, j) = E((X_i - \mu_i) \times (X_j - \mu_j)')
\]
For a stationary process, the auto-covariance depends only on the lag, |i - j|.
|
| Modifier and Type | Class and Description |
|---|---|
class |
VARMAAutoCorrelation
Compute the Auto-Correlation Function (ACF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that
\(EX_{t} = 0\).
|
class |
VARMAAutoCovariance
Compute the Auto-CoVariance Function (ACVF) for a vector AutoRegressive Moving Average (ARMA) model, assuming that
\(EX_{t} = 0\).
|
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