[R-SIG-Finance] re[R-sig-finance] gression problem

[Bogaso]

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
nature


rechtsteiner wrote:
> 
> 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!
> 
> josuah
> 
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