[R-SIG-Finance] re[R-sig-finance] gression problem
bogaso.christofer at gmail.com
Tue Mar 10 10:10:05 CET 2009
You might try MLE, construct the liklihood function and then optimize it by
experimenting different choices of parameters. I have doubt how LS
estimation procedure can be employed here as parameters are nonlinear in
> dear useRs,
> i'm working with a mean reverting model of the following specification:
> y = mu + beta(x - mu) + errorterm, where mu is a constant
> currently I estimate just y = x (with lm()) to get beta and then
> calculate mu = estimated intercept / (1-beta).
> but I'd like to estimate mu and beta together in one regression-step
> and also get the test-statistics (including parameter variance) for mu
> as well as for beta in the summary of the regression.
> could you please help me?
> thanks very much in advance!
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