Hi all R gurus out there, Im a kind of newbie to kalman-filters after some research I have found that the dlm package is the easiest to start with. So be patient if some of my questions are too basic.
I would like to set up a beta estimation between an asset and a market index using a kalman-filter. Much littarture says it gives superior estimates compared to OLS estimates. So I would like to learn and to use the filter. I would like to run two types of kalman-filters, one with using a random-walk model (RW) and one with a stationary model, in other worlds the transition equition either follow a RW or AR(1) model. This is how I think it would be set up; I will have my time-series Y,X, where Y is the response variable this setup should give me a RW process if I have understood the example correctly mydlmModel = dlmModReg(X) + dlmModPoly(order=1) and then run on the dlm model dlmFilter(Y,mydlmModel ) but setting up a AR(1) process is unclear, should I use dlmModPoly or the dlmModARMA to set up the model. And at last but not the least, how do I set up a proper build function to use with dlmMLE to optimize the starting values. Regards Tom -- View this message in context: http://www.nabble.com/Help-with-kalman-filterd-betas-using-the-dlm-package-tp23473796p23473796.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.