uGMAR (version 3.2.6)

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

Description

get_regime_means calculates the regime means \(\mu_{m} = \phi_{m,0}/(1-\sum\phi_{i,m})\) for the given GMAR, StMAR, or G-StMAR model

Usage

get_regime_means(gsmar)

Arguments

gsmar

object of class 'gsmar' created with the function fitGSMAR or GSMAR.

Value

Returns a length M vector containing the regime mean \(\mu_{m}\) in the m:th element.

References

• Kalliovirta L., Meitz M. and Saikkonen P. 2015. Gaussian Mixture Autoregressive model for univariate time series. Journal of Time Series Analysis, 36, 247-266.

• Meitz M., Preve D., Saikkonen P. 2018. A mixture autoregressive model based on Student's t-distribution. arXiv:1805.04010 [econ.EM].

• Virolainen S. 2020. A mixture autoregressive model based on Gaussian and Student's t-distribution. arXiv:2003.05221 [econ.EM].

See Also

condMoments, uncondMoments, get_regime_vars, get_regime_autocovs

Other moment functions: condMoments(), get_regime_autocovs(), get_regime_vars(), uncondMoments()

Examples

# NOT RUN {
# GMAR model
params13 <- c(1.4, 0.88, 0.26, 2.46, 0.82, 0.74, 5.0, 0.68, 5.2, 0.72, 0.2)
gmar13 <- GSMAR(p=1, M=3, params=params13, model="GMAR")
get_regime_means(gmar13)

# StMAR model
params12t <- c(1.38, 0.88, 0.27, 3.8, 0.74, 3.15, 0.8, 100, 3.6)
stmar12t <- GSMAR(p=1, M=2, params=params12t, model="StMAR")
get_regime_means(stmar12t)

# G-StMAR model (similar to the StMAR model above)
params12gs <- c(1.38, 0.88, 0.27, 3.8, 0.74, 3.15, 0.8, 3.6)
gstmar12 <- GSMAR(p=1, M=c(1, 1), params=params12gs, model="G-StMAR")
get_regime_means(gstmar12)
# }