Hello, i'm currently working with the 'garch' function provided by the 'tseries' package in R.
If you want to fit a time series you can call the function this way fit = garch(data, order=c(1,1)). A GARCH model delivers you a vector of sd's sigma and therefore confidence intervals for your data. You can get them from the function output by calling fit$fitted.values. You can also get some kind of residuals with fit$residuals and here is my question: does anybody know how they are computed? Normally some would say residuals = data - model, but for GARCH modelling there is no exact model for the data but the confidence interval mentioned above. To compare the residuals I got here from the GARCH modelling to other models I really need to know how they are computed, but the R documentary doesn't provide an answer. Anyone got a clue? Thanks for any help in advance. -- View this message in context: http://r.789695.n4.nabble.com/Residuals-in-garch-tseries-tp4677241.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
