quantile_residual_plot {uGMAR}

Plot quantile residual time series and histogram

Description

quantile_residualsPlot plots quantile residual time series and histogram.

Usage

quantile_residual_plot(gsmar)

Arguments

gsmar

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

Value

Only plots to a graphical device and doesn't return anything.

References

• Galbraith, R., Galbraith, J. 1974. On the inverses of some patterned matrices arising in the theory of stationary time series. Journal of Applied Probability 11, 63-71.

• Kalliovirta L. (2012) Misspecification tests based on quantile residuals. The Econometrics Journal, 15, 358-393.

• 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

profile_logliks, diagnostic_plot, fitGSMAR, GSMAR, quantile_residual_tests, simulate.gsmar

Examples

## The below examples the approximately 15 seconds to run.

# G-StMAR model with one GMAR type and one StMAR type regime
fit42gs <- fitGSMAR(M10Y1Y, p=4, M=c(1, 1), model="G-StMAR",
                    ncalls=1, seeds=4)
quantile_residual_plot(fit42gs)

# GMAR model
fit12 <- fitGSMAR(data=simudata, p=1, M=2, model="GMAR", ncalls=1, seeds=1)
quantile_residual_plot(fit12)