Perform a goodness-of-fit test for the GARCH model by checking whether the standardized residuals are iid based on the ACF of the absolute residuals or squared residuals.
gBox(model, lags = 1:20, x, method = c("squared", "absolute")[1], plot = TRUE)fitted model from the garch function of the tseries library
a vector of maximum ACF lags to be used in the test
time series data to which the GARCH model is fitted
"squared": test is based on squared residuals; "absolute": test is based on absolute residuals
logical variable, if TRUE, the p-values of the tests are plotted
lags in the input
a vector of p-values of the tests
method used
x
"Time Series Analysis, with Applications in R" by J.D. Cryer and K.S. Chan
# NOT RUN {
# library(tseries) # need to uncomment this line when running the example
data(CREF)
r.cref=diff(log(CREF))*100
m1=garch(x=r.cref,order=c(1,1))
summary(m1)
#gBox(m1,x=r.cref,method='squared')
# }
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