About my previous posting asking for information about intervention
analysis:
I just realized that my time series have not only steps in the mean, but
also changes in the variance.
It also has significant autocorrelation characteristics.
I'm thinking of using a combined GARCH, intervention model to take into
accound the heteroskedasticity, but I'm not sure that is the best way.
I also have a reference to use Bayes regression using Gibbs sampling
approach (a way to estimate parameters for heteroskedastic models with AR(k)
characteristics).
Am I in the right track?
Thank you
Hugo
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--
Hugo Hidalgo-Leon
Water Resources Program.
Civil & Environmental Engineering Department.
School of Engineering and Applied Science.
University of California, Los Angeles.
5731/5732 Boelter Hall.
UCLA box 951593
Los Angeles, CA 90095-1593
[EMAIL PROTECTED]
(310) 206 8612 Voice
(310) 206 7245 Fax
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