Re: st: RE: using bootstrap for sample splitting and out-of-sample prediction

[Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>]

Not entirely sure, but I think your use of -clear- within the
-program- was having an adverse effect:
*********************************************
clear*
set obs 10000
gen x=rnormal()
gen y=2+3*x+rnormal()
capt prog drop myprog
prog myprog, rclass
       vers 11
	cap drop forsort
	cap drop res
       gen forsort=runiform()
       sort forsort
       reg y x in 1/5000
       predict res, res
       su res in 5001/10000, mean
       return scalar mean=r(mean)
end
bs mean=r(mean), reps(100) nodrop: myprog
*********************************************

T

2010/4/27 Martin Weiss <martin.weiss1@gmx.de>:
>
> <>
>
> Try this: (BTW, why is it not possible to -bootstrap r(mean), reps(50)
> nodrop: myprog- on this thing? I have now searched for a solid hour for my
> mistake, and cannot find it...)
>
> *******
>
>
> clear*
> set obs 10000
> gen x=rnormal()
> //true model
> gen y=2+3*x+rnormal()
> sa myfile, replace
>
>
> capt prog drop myprog
>
> prog myprog
>        vers 10.1
>        u myfile, clear
>        gen forsort=runiform()
>        sort forsort
>        reg y x in 1/5000
>        predict res, res
>        su res in 5001/10000, mean
> end
>
>
> tempname hdle
> tempfile info
> postfile `hdle' iteration mean using `info'
>
> qui forv i=0/1000{
>        myprog
>        post `hdle' (`i') (r(mean))
>  }
>
> postclose `hdle'
>
> use `info', clear
> l, abbrev(12) noobs sep(0)
>
>
>
> *
> *bs mean=r(mean), reps(200) nodrop: myprog
> *******
>
>
> HTH
> Martin
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Lin, Bill
> Sent: Montag, 26. April 2010 22:54
> To: statalist@hsphsun2.harvard.edu
> Subject: st: using bootstrap for sample splitting and out-of-sample
> prediction
>
> Hello All,
>
> I am trying to split my sample into two halves, use one half for
> estimation and another half for out-of sample prediction, and then
> calculate the average difference between fitted values and the
> observed values. I want to do it repeatedly, say 1000 times, using
> bootstrap. My problem is that I don't know how to store the average
> difference calculated each time in a matrice as in Matlab. Can any one
> give some suggestions? thanks,
>
>
> Bill Lin
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-- 
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recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
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