gmvarkit (version 1.1.1)

get_regime_means: Calculate regime means \(\mu_{m}\)

Description

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

Usage

get_regime_means(gmvar)

Arguments

gmvar

object of class 'gmvar' created with fitGMVAR or GMVAR.

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.

• Lutkepohl H. 2005. New Introduction to Multiple Time Series Analysis, Springer.

See Also

uncond_moments, get_regime_autocovs, cond_moments

Other moment functions: cond_moments, get_regime_autocovs, uncond_moments

Examples

# NOT RUN {
# These examples use the data 'eurusd' which comes with the
# package, but in a scaled form.
data <- cbind(10*eurusd[,1], 100*eurusd[,2])
colnames(data) <- colnames(eurusd)

# GMVAR(1,2), d=2 model:
params122 <- c(0.623, -0.129, 0.959, 0.089, -0.006, 1.006, 1.746,
 0.804, 5.804, 3.245, 7.913, 0.952, -0.037, -0.019, 0.943, 6.926,
 3.982, 12.135, 0.789)
mod122 <- GMVAR(data, p=1, M=2, params=params122)
mod122
get_regime_means(mod122)


# GMVAR(2,2), d=2 model with mean-parametrization:
params222 <- c(-11.904, 154.684, 1.314, 0.145, 0.094, 1.292, -0.389,
 -0.070, -0.109, -0.281, 0.920, -0.025, 4.839, 11.633, 124.983, 1.248,
  0.077, -0.040, 1.266, -0.272, -0.074, 0.034, -0.313, 5.855, 3.570,
  9.838, 0.740)
mod222 <- GMVAR(data, p=2, M=2, params=params222, parametrization="mean")
mod222
get_regime_means(mod222)
# }