Steady-State Covariance Matrix for the Observed Variables in the State Space Model
Source:R/simStateSpace-ssm-cov-y.R
SSMCovY.RdThe steady-state covariance matrix for the observed variables in the state space model \(\mathrm{Cov} \left( \mathbf{y} \right)\) is given by $$ \mathrm{Cov} \left( \mathbf{y} \right) = \boldsymbol{\Lambda} \mathrm{Cov} \left( \boldsymbol{\eta} \right) \boldsymbol{\Lambda}^{\prime} + \boldsymbol{\Theta} $$ where \(\boldsymbol{\Lambda}\) is the matrix of factor loadings, \(\boldsymbol{\Theta}\) is the covariance matrix of the measurement error, and \(\mathrm{Cov} \left( \boldsymbol{\eta} \right)\) is the steady-state covariance matrix for the latent variables.
Arguments
- lambda
Numeric matrix. Factor loading matrix linking the latent variables to the observed variables (\(\boldsymbol{\Lambda}\)).
- theta
Numeric matrix. The covariance matrix of the measurement error (\(\boldsymbol{\Theta}\)).
- cov_eta
Numeric matrix. The steady-state covariance matrix for the latent variables in the state space model
See also
Other Simulation of State Space Models Data Functions:
LinSDE2SSM(),
LinSDECovEta(),
LinSDECovY(),
LinSDEMeanEta(),
LinSDEMeanY(),
ProjectToHurwitz(),
ProjectToStability(),
SSMCovEta(),
SSMMeanEta(),
SSMMeanY(),
SimAlphaN(),
SimBetaN(),
SimBetaN2(),
SimCovDiagN(),
SimCovN(),
SimIotaN(),
SimNuN(),
SimPhiN(),
SimPhiN2(),
SimSSMFixed(),
SimSSMIVary(),
SimSSMLinGrowth(),
SimSSMLinGrowthIVary(),
SimSSMLinSDEFixed(),
SimSSMLinSDEIVary(),
SimSSMOUFixed(),
SimSSMOUIVary(),
SimSSMVARFixed(),
SimSSMVARIVary(),
SpectralRadius(),
TestPhi(),
TestPhiHurwitz(),
TestStability(),
TestStationarity()
Examples
beta <- matrix(
data = c(
0.7, 0.5, -0.1,
0.0, 0.6, 0.4,
0.0, 0.0, 0.5
),
nrow = 3
)
psi <- 0.1 * diag(3)
lambda <- diag(3)
theta <- diag(3)
cov_eta <- SSMCovEta(
beta = beta,
psi = psi
)
SSMCovY(
lambda = lambda,
theta = theta,
cov_eta = cov_eta
)
#> [,1] [,2] [,3]
#> [1,] 1.19607843 0.1183232 0.02985385
#> [2,] 0.11832319 1.3437711 0.13818551
#> [3,] 0.02985385 0.1381855 1.26638284