Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
SymmetricSVD.U()
Returns the matrix U as in A=UDV'.
|
ImmutableMatrix |
SymmetricSVD.Ut()
Returns the matrix U' as in A=UDV'.
|
ImmutableMatrix |
SymmetricSVD.V()
Returns the matrix V as in A=UDV'.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LSProblem.A()
Gets the homogeneous part, the coefficient matrix, of the linear system.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
Pow.B()
Get the double precision matrix.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
R1toConstantMatrix.evaluate(double x) |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
QuadraticFunction.Hessian() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LinearConstraints.A()
Get the constraint coefficients.
|
Modifier and Type | Field and Description |
---|---|
ImmutableMatrix |
CentralPath.S
This is the auxiliary helper to solve the dual problem.
|
ImmutableMatrix |
CentralPath.X
This is the minimizer for the primal problem.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LPProblemImpl1.A() |
ImmutableMatrix |
LPProblem.A()
Get the coefficients, A, of the greater-than-or-equal-to constraints A * x ≥ b.
|
ImmutableMatrix |
LPProblemImpl1.Aeq() |
ImmutableMatrix |
LPProblem.Aeq()
Get the coefficients, Aeq, of the equality constraints Aeq * x ≥ beq.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LPRevisedSimplexSolver.Problem.A() |
ImmutableMatrix |
LPRevisedSimplexSolver.Problem.Aeq() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
QPProblem.A()
Get the coefficients of the inequality constraints: A as in \(Ax \geq b\).
|
ImmutableMatrix |
QPProblem.Aeq()
Get the coefficients of the equality constraints: Aeq as in \(A_{eq}x = b_{eq}\).
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
ILPProblemImpl1.A() |
ImmutableMatrix |
ILPProblemImpl1.Aeq() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LedoitWolf2004.Result.F()
Gets the sample constant correlation matrix F.
|
ImmutableMatrix |
LedoitWolf2004.Result.S()
Gets the sample covariance matrix S.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
CovarianceSelectionProblem.S()
Gets the original sample covariance matrix.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LedoitWolf2016.Result.S()
Sample covariance matrix.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
MultivariateDLM.C0()
Get the covariance matrix of x0.
|
ImmutableMatrix |
MultivariateObservationEquation.F(int t)
Gets F(t), the coefficient matrix of xt.
|
ImmutableMatrix |
MultivariateLinearKalmanFilter.getFittedStateVariance(int t)
Get the posterior expected state variance.
|
ImmutableMatrix |
MultivariateLinearKalmanFilter.getKalmanGain(int t)
Get the Kalman gain.
|
ImmutableMatrix |
MultivariateLinearKalmanFilter.getPredictedObservationVariance(int t)
Get the prior observation prediction variance.
|
ImmutableMatrix |
MultivariateLinearKalmanFilter.getPredictedStateVariance(int t)
Get the prior expected state variance.
|
ImmutableMatrix |
MultivariateObservationEquation.V(int t)
Gets V(t), the covariance matrix of vt.
|
ImmutableMatrix |
MultivariateStateEquation.xt_var(int t,
Matrix var_tlag_tlag)
Gets the variance of the apriori prediction for the next state.
|
ImmutableMatrix |
MultivariateObservationEquation.yt_var(int t,
Matrix var_t_tlag)
Gets the covariance of the apriori prediction for the next observation.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
FAEstimator.loadings()
Gets the rotated loading matrix.
|
ImmutableMatrix |
FactorAnalysis.S()
Gets the covariance (or correlation) matrix.
|
ImmutableMatrix |
FAEstimator.scores()
Gets the matrix of scores, computed using either Thompson's (1951)
scores, or Bartlett's (1937) weighted least-squares scores.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
DiscreteHMM.B()
Gets the conditional probabilities of the observation symbols: rows
correspond to state; columns corresponds symbols.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
SimpleMC.A()
Gets the state transition probabilities.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LMProblem.A()
Gets the regressor matrix.
|
abstract ImmutableMatrix |
LMBeta.covariance()
Gets the covariance matrix of the coefficient estimates, β^.
|
ImmutableMatrix |
LMProblem.invOfwAtwA()
(wA' * wA)-1
|
ImmutableMatrix |
LMProblem.wA()
Gets the weighted regressor matrix.
|
ImmutableMatrix |
LMProblem.X()
Gets the factor matrix.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
GLMBeta.covariance() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
QuasiGLMBeta.covariance() |
ImmutableMatrix |
QuasiGLMNewtonRaphson.D()
Computes D.
|
ImmutableMatrix |
QuasiGLMNewtonRaphson.DVInv()
Computes D / V(μ).
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LogisticBeta.covariance() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
OLSBeta.covariance() |
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
LMResiduals.hHat()
Gets the projection matrix, H-hat.
|
Modifier and Type | Field and Description |
---|---|
ImmutableMatrix |
AS159.RandomMatrix.A
a random matrix constructed by AS159
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
VARIMAXModel.AR(int i)
Get the i-th AR coefficient; AR(0) = 1.
|
ImmutableMatrix |
VARIMAXModel.MA(int i)
Get the i-th MA coefficient; MA(0) = 1.
|
ImmutableMatrix[] |
VARIMAXModel.phi()
Get all the AR coefficients.
|
ImmutableMatrix |
VARIMAXModel.psi()
Get the coefficients of the deterministic terms.
|
ImmutableMatrix |
VARIMAXModel.sigma()
Get the white noise covariance matrix.
|
ImmutableMatrix[] |
VARIMAXModel.theta()
Get all the MA coefficients.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
MultivariateInnovationAlgorithm.covariance(int n)
Get the covariance matrix for prediction errors at time t for x^t+1.
|
ImmutableMatrix |
MultivariateForecastOneStep.covariance(int n)
Get the covariance matrix for prediction errors for \(\hat{x}_{n+1}\), made at time n.
|
ImmutableMatrix |
MultivariateInnovationAlgorithm.theta(int i,
int j)
Get the coefficients of the linear predictor.
|
ImmutableMatrix |
MultivariateForecastOneStep.theta(int i,
int j)
Get the coefficients of the linear predictor.
|
Modifier and Type | Method and Description |
---|---|
ImmutableMatrix |
VARMAForecastOneStep.covariance(int n)
Get the covariance matrix for prediction errors for \(\hat{x}_{n+1}\), made at time n.
|
ImmutableMatrix[] |
VECM.gamma()
Get the AR coefficients of the lagged differences;
null if p = 1 |
ImmutableMatrix |
VECM.gamma(int i)
Get the AR coefficient of the i-th lagged differences.
|
ImmutableMatrix |
VECM.pi()
Get the impact matrix.
|
ImmutableMatrix |
VECM.psi()
Get the coefficients of the deterministic terms.
|
ImmutableMatrix |
VECM.sigma()
Get the white noise covariance matrix.
|
ImmutableMatrix |
VARMAForecastOneStep.theta(int i,
int j)
Get the coefficients of the linear predictor.
|
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