uGMAR (version 3.5.2)

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)

Value

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

Arguments

gsmar

a class 'gsmar' object, typically generated by fitGSMAR or GSMAR.

References

• Kalliovirta L., Meitz M. and Saikkonen P. 2015. Gaussian Mixture Autoregressive model for univariate time series. Journal of Time Series Analysis, 36(2), 247-266.

• Meitz M., Preve D., Saikkonen P. 2023. A mixture autoregressive model based on Student's t-distribution. Communications in Statistics - Theory and Methods, 52(2), 499-515.

• Virolainen S. 2022. A mixture autoregressive model based on Gaussian and Student's t-distributions. Studies in Nonlinear Dynamics & Econometrics, 26(4) 559-580.

See Also

cond_moments, uncond_moments, get_regime_vars, get_regime_autocovs

Other moment functions: cond_moments(), get_regime_autocovs(), get_regime_vars(), uncond_moments()

Examples

# 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)