Re: st: locally weighted regression with weighted data

[Prashant <presearchwork@gmail.com>]

With all deference to previous comments, I think also that the
user-written command locreg can take weights -- it is downloadable
using:
net install ivqte, from("http://www.econ.brown.edu/fac/Blaise_Melly/";)

best,
Prashant


On Sat, Jan 8, 2011 at 1:59 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> It's easier (e.g.) to construct your own set of spline predictors with -mkspline- and then call up -regress- directly. Then you can have any weights you want.
>
> Tastes and experiences will vary -- a lot -- but for a default regression-type smooth I typically now prefer fractional polynomial or cubic spline regressions, rather than any kernel method, such as lowess (loess) or local polynomials.
>
> They tend to be smoother (informally) and faster and come equipped with confidence interval machinery -- to be treated sceptically rather than deferentially, of course.
> Also, you can combine with other predictors.
>
> Nick
> n.j.cox@durham.ac.uk
>
> Jorge Eduardo Pérez Pérez
>
> You could bin your x variable and calculate weighted means of the y
> variable for each bin, then run -lowess- on the means. This is the
> approach used in the following article, although it is used to local
> polinomial regression (command -lpoly-).
>
> D. R. Bellhouse and J. E. Stafford. Local polynomial regression in complex
> survey. Survey Methodology, 27(2):197–203, 2001.
>
> Florian Scheuer
>
>> does anyone know how to run a locally weighted regression with weighted data? the stata command 'lowess' does not allow for weights.
>
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