View source: R/diagnosticPlot.R
quantile_residual_plot | R Documentation |
quantile_residualsPlot
plots quantile residual time series and histogram.
quantile_residual_plot(gsmar)
gsmar |
a class 'gsmar' object, typically generated by |
Only plots to a graphical device and doesn't return anything.
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.
profile_logliks
, diagnostic_plot
, fitGSMAR
, GSMAR
,
quantile_residual_tests
, simulate.gsmar
## 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.