Ana--
I would advise degree 1, for local linear regression, and note that
the kernel makes little difference, whereas the bandwidth is crucially
important. With a large enough bandwidth, you will get -tw lfit- and
with a small enough bandwidth, you will get -tw line-.
On Jan 23, 2008 2:52 PM, Nick Cox <[email protected]> wrote:
> I don't know what best to advise, but more importantly there's a very
> large associated literature that gives lots of guidance. What I do
> notice is that there are three main choices, the kernel, the bandwidth
> and the degree.
>
> I've found restricted cubic splines, as implemented, in Stata 10, within
>
> -mkspline-, much easier to handle. It's true that under that the knot
> positions (and so the number of knots) need to be specified, but the
> default positions for a given number of knots in my experience alweays
> work well.
>
> There is a wrapper program to make it easier on SSC as -rcspline-.
>
> Nick
> [email protected]
>
> Ana R. Rios
>
> I was wondering if there is any guideline for choosing
> the degree of the polynomial to be used in the
> smoothing (degree(#) option in lpoly).
>
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