-kernreg2-, of which I am notionally first
author, was intended to be a temporary fix
of -kernreg-, written by other people.
It didn't turn out that way, but no matter:
-locpoly- is now the recommended command,
in my view. In short, -kernreg2- is history,
except that it remains in the archives out
of inertia and for people still on earlier
versions of Stata.
However, both of them stop a long way short
of offering this kind of functionality.
Having said that, my own personal view is
that kernel regression is not obviously
the best thing for summarising how a
binary response varies with a predictor.
I can't offer more positive advice because
I am unclear on how far your problem is
tractable at all.
Nick
[email protected]
Eik Leong Swee
> I am trying to do a kernel density estimation of a y ( a 0-1 variable)
> on x1. This generates Graph1. I also did an estimation on y on x2 and
> generated graph2. I used kernreg2 for both these estimations.
>
> Now, I would also like to bootstrap confidence intervals around the
> graph and subsequently test the two distributions from graph 1 and 2
> (to see if they are statistically different in the relevant range) .
> Unfortunately, kernreg2 does not give the non-parametric standard
> errors. I tried bootstrapping nevertheless, and this is the output
> that I get.
> Bootstrap statistics
>
> Variable | Reps Observed Bias Std. Err. [95% Conf. Interval]
> ---------+----------------------------------------------------
> ---------------
> klnpce | 100 10.69125 .5342394 .9190264 8.867703 12.5148 (N)
> | 9.449879 13.2954 (P)
> | 9.095177 11.76517 (BC)
> --------------------------------------------------------------
> ---------------
> N = normal, P = percentile, BC = bias-corrected
>
>
> First I would like to draw confidence intervals for the entire
> function, and then bootstrap the confidence intervals and am not sure
> how to do it. I was wondering if anyone had faced this problem, and
> could help me out.
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
