I am a bit lost on what you are trying to do
here. You seem to be generating samples from
a normal, but only wanting to keep them if they appear
really close to the target population
in the sense that sample mean and sample sd
are really close to the corresponding population
parameters.
If that's right and memory is the issue, then
you should test each sample just after generation
and drop it immediately if it is not up to your
standards. Or equivalently you could do something
like this:
gen prov = .
local j = 1
qui while `j' < 100 {
replace prov = 50 + 10 * invnorm(uniform())
su prov
if inrange(r(mean),49.9,50.1)) & inrange(r(sd),9.9,10.1) {
gen OK`j++' = prov
}
}
That way, what you have in memory is just
the last sample generated
and all previous samples generated deemed OK
By the way, standard advice in the Statalist FAQ is
The current version of Stata is 8.2. Please specify if
you are using an earlier version; otherwise, the answer
to your question is likely to refer to commands or
features unavailable to you.
Nick
[email protected]
P.S. Stata is telling you why your code didn't work. First
time round it thinks that the
[1]
in
use ai[1].dta, clear
is a reference to weights. This also is puzzling. Presumably
you wouldn't try to -use- that dataset if you hadn't previously
saved it, but is that a legal filename with your (unstated)
operating system?
--------------------------------------------------------------
victor michael zammit
> the following dataset lists the 16 variables , out of 1000 normally
> distributed variable with mean 50 and standard deviation 10
> , and then <
> keep if mean>49.9 & mean < 50.1 & sd > 9.9 & sd< 10.1 > . I
> would like to
> do this for different < set obs # > ,and 10,000 instead of
> 1000 , but
> memory becomes an issue .What I thought I could do , is to
> save variable i
> ' s under a different name, and then go to the next <set
> obs #> and <
> save,replace> over the previous 1000 or whatever variables .
>
> +---------------------------+
> mean sd i
> ---------------------------
> 1. 49.96996 9.978514 76
> 2. 49.92636 10.07861 118
> 3. 49.97271 10.07149 122
> 4. 50.07562 10.07239 218
> 5. 49.94316 9.913686 220
> ---------------------------
> 6. 50.02873 10.05811 346
> 7. 50.01596 10.04384 442
> 8. 50.00026 9.943673 513
> 9. 49.91186 9.95947 533
> 10. 50.00311 10.00525 629
> ---------------------------
> 11. 50.09705 9.929688 653
> 12. 49.98079 10.04592 678
> 13. 49.93727 9.962771 686
> 14. 49.98563 10.07247 694
> 15. 50.08827 9.936735 833
> ---------------------------
> 16. 49.97584 10.05994 854
>
>
> I experimented with a loop :
>
>
> . local i = 1
>
> . while `i'<= _N {
> 2. use ai[`i'].dta,clear
> 3. save b`i',replace
> 4. local i = `i'+1
> 5. }
> weights not allowed
> r(101);
>
> but it did not work
> Is there a way I could do this ?
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