Hi there, I'm working with a time series that has a clear seasonal component in it's conditional distribution. Not only does the variance increase at certain parts of the seasonal cycle, but also the distribution becomes skewed.
I would like to fit an fGarch model to this time series, but with a conditional distribution which depends on a dummy variable. I was wondering if anyone knew if this was possible in fGarch or any of the similar packages? /(As an aside, I recognise that this may not be the easiest way to go about modelling this. For a little more detail: This is a time series with a strong diurnal cycle in it. The series has been 'detrended' and is stationary at least under the usual metrics. However, still clearly during the midnight hours, the residuals are strongly positively skewed. I have tried transforming the series, but the large disparity in both the skew and scale see to prohibit this working nicely. Any other suggestions are welcome)/ -- View this message in context: http://r.789695.n4.nabble.com/Changing-seasonal-conditional-distribution-in-a-fGarch-model-tp4690850.html Sent from the Rmetrics mailing list archive at Nabble.com. _______________________________________________ R-SIG-Finance@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.