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Re: st: RE: lpoly

From   "Austin Nichols" <[email protected]>
To   [email protected]
Subject   Re: st: RE: lpoly
Date   Wed, 23 Jan 2008 15:02:50 -0500

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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