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st: RE: How to plot bootstrap CI for the entire kernel estimation of y on x?

From   "Nick Cox" <>
To   <>
Subject   st: RE: How to plot bootstrap CI for the entire kernel estimation of y on x?
Date   Fri, 4 Feb 2005 15:16:54 -0000

-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. 


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.

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