R: Calculate regime means mu

get_regime_means {gmvarkit}

R Documentation

Calculate regime means `\mu_{m}`

Description

get_regime_means calculates regime means \mu_{m} = (I - \sum A_{m,i})^(-1)) for the given GMVAR, StMVAR, or G-StMVAR model.

Usage

get_regime_means(gsmvar)

Arguments

gsmvar

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

Value

Returns a (dxM) matrix containing regime mean \mu_{m} in the m:th column, m=1,..,M.

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 Unpublished working paper, available as arXiv:2109.13648.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(1,2), d=2 model:
params12 <- c(0.55, 0.112, 0.344, 0.055, -0.009, 0.718, 0.319, 0.005,
 0.03, 0.619, 0.173, 0.255, 0.017, -0.136, 0.858, 1.185, -0.012,
 0.136, 0.674)
mod12 <- GSMVAR(gdpdef, p=1, M=2, params=params12)
mod12
get_regime_means(mod12)

# Structural GMVAR(2, 2), d=2 model identified with sign-constraints:
params22s <- c(0.36, 0.121, 0.484, 0.072, 0.223, 0.059, -0.151, 0.395,
 0.406, -0.005, 0.083, 0.299, 0.218, 0.02, -0.119, 0.722, 0.093, 0.032,
 0.044, 0.191, 0.057, 0.172, -0.46, 0.016, 3.518, 5.154, 0.58)
W_22 <- matrix(c(1, 1, -1, 1), nrow=2, byrow=FALSE)
mod22s <- GSMVAR(gdpdef, p=2, M=2, params=params22s, structural_pars=list(W=W_22))
mod22s
get_regime_means(mod22s)

[Package gmvarkit version 2.1.2 Index]

Calculate regime means \mu_{m}