[R-SIG-Finance] Help on constrained regression
rhelpacc at gmail.com
Fri Jul 3 01:36:50 CEST 2009
I did. The problem was the underlying process that's negative AR(1).
So I just have to find other way to model it. Thank you.
On Thu, Jul 2, 2009 at 7:31 PM, spencerg<spencer.graves at prodsyse.com> wrote:
> Have you considered writing the model in terms of log(a) = g, say:
> y[t] = exp(g)*y[t-1]+b+epsilon?
> With this, you could estimate "g" and "b" using "nls". With multiple
> series, you could use the "nlme" function in the "nmle" package. For the
> "nlme" package, an excellent reference in Pinheiro and Bates (2000)
> Mixed-Effects Models in S and S-PLUS (Springer).
> Hope this helps.
> Spencer Graves
> R_help Help wrote:
>> I have an AR(1) model
>> y[t] = ay[t-1]+b+epsilon
>> I'm trying to force a to be positive. So I did the constrained
>> regression with constraints 0 < a < 1. I used pcls in package mgcv.
>> However, I found that the solution is not so stable. Most of my lag 1
>> autocorrelation is negative. Forcing a to positive value makes the
>> optimizer to stick a to the boundary value. All it does is varying b.
>> I there anyway to solve this problem? I think the problem might be due
>> to my initial value is not a smart choice.
>> Thank you.
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