Re: st: Re: Linear regression using Mata optimize

[Nicola Orsini <nicola.orsini@ki.se>]

Martin,

of course I know many other ways I could fit a linear regression model.
However, my question was on the use of optmize(). I don't want to avoid 
it, I just want to better understand how it works.

Nicola

Martin Weiss wrote:
> <>
>
> Here`s a solution that avoids all the rocket science:
> -help m1_interactive-
>
>
> HTH
> Martin _______________________
> ----- Original Message ----- From: "Nicola Orsini" <Nicola.Orsini@ki.se>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Monday, February 09, 2009 6:10 PM
> Subject: st: Linear regression using Mata optimize
>
>
> > My question is why I'm not getting the correct variance-covariance  
> > matrix in the example below (simple linear regression) when using  
> > optimize_result_V(S).
> > Any thoughts on this?
> >
> > Nicola
> >
> > /* Linear regression using Mata optimize */
> >
> > sysuse auto, clear
> >
> > local xlist mpg cons
> >
> > mata
> >
> > st_view(x=0,.,("mpg"))
> > st_view(y=0,.,("price"))
> > x=x,J(rows(x),1,1)
> >
> > void olsest(todo, b, y, x, lf, g, H)
> > {
> > e = (y-x*b')
> > lf = -(e'*e)
> > }
> >
> >   S = optimize_init()
> >   optimize_init_evaluator(S, &olsest())
> >   optimize_init_evaluatortype(S, "v0")
> >   optimize_init_argument(S, 1, y)
> >   optimize_init_argument(S, 2, x)
> >   optimize_init_params(S, J(1,cols(x),0))
> >
> >   optimize_init_which(S,"max")
> >
> >   betahat = optimize(S)
> >   vhat = optimize_result_V(S)
> >
> >   st_matrix("b", betahat)
> >   st_matrix("V", vhat)
> >
> > end
> >
> > matrix colnames b = `xlist'
> > matrix colnames V = `xlist'
> > matrix rownames V = `xlist'
> >
> > ereturn post b V , dep(price)
> > ereturn di
> >
> > reg price mpg
> >
> > exit
> >
> >
> > *
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> *
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*
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