get_omega_eigens {gmvarkit}

Calculate the eigenvalues of the "Omega" error term covariance matrices

Description

get_omega_eigens calculates the eigenvalues of the "Omega" error term covariance matrices for each mixture component.

Usage

get_omega_eigens(gsmvar)

Arguments

gsmvar

an object of class 'gsmvar', typically created with fitGSMVAR or GSMVAR.

Value

Returns a matrix with d rows and M columns - one column for each regime. The mth column contains the eigenvalues of the "Omega" error term covariance matrix of the mth regime.

References

• Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485-498.

• Virolainen S. (forthcoming). A statistically identified structural vector autoregression with endogenously switching volatility regime. Journal of Business & Economic Statistics.

• Virolainen S. 2022. Gaussian and Student's t mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks in the Euro area. Unpublished working paper, available as arXiv:2109.13648.

@keywords internal

Examples

# GMVAR(2, 2), d=2 model
params22 <- c(0.36, 0.121, 0.223, 0.059, -0.151, 0.395, 0.406, -0.005,
 0.083, 0.299, 0.215, 0.002, 0.03, 0.484, 0.072, 0.218, 0.02, -0.119,
  0.722, 0.093, 0.032, 0.044, 0.191, 1.101, -0.004, 0.105, 0.58)
mod22 <- GSMVAR(p=2, M=2, d=2, params=params22)
get_omega_eigens(mod22)