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RE: st: RE: Re: corr() with weights, -by-

From   "Nick Cox" <>
To   <>
Subject   RE: st: RE: Re: corr() with weights, -by-
Date   Sun, 8 Jun 2008 17:05:02 +0100

Using -statsby- and the other approach are strictly solutions to
different problems. 

-statsby- is what has been called a reduction command. It can be clever
about doing repeated -if- selections, by virtue of suggestions made by
Michael himself. There is nothing in my code that is clever on that

I doubt that using -levelsof- is outstandingly inefficient in machine
time as such; it's just that it is unnecessary. 


Philipp Rehm

Thanks, Nick.
That's a good idea, too.
I haven't compared the efficiency of Michael's and your solution. But 
given that I have 162 county-years with a total of around 3.5 million 
observations, either solution should be much much more efficient than my

-levelsof- approach.

Nick Cox wrote:
> On the other hand, if you want the covariances alongside the data,
> approach is cleaner than recourse to -levelsof-: 
> gen cov = . 
> egen group = group(country year) 
> su group, meanonly 
> quietly forval i = 1/`r(max)' { 
> 	corr x l2.x [aw=weight] if group == `i', cov 
> 	replace cov = r(cov_12) if group == `i' 
> } 
> See also 
> FAQ     . . . . . . . . . . Making foreach go through all values of a
> variable
>         8/05    Is there a way to tell Stata to try all values of a
>                 particular variable in a foreach statement without
>                 specifying them?
> However, -statsby- and then using -merge- may be just as efficient. 
> Michael Blasnik
> ...
> You  want the -statsby- command.  Something like this work:
> statsby cov=r(cov_12), by(year country) : corr x l2.x  [aw= weight],
> Philipp Rehm
>> I am looking for an efficient way to extract weighted covariances,
> a 
>> by-able problem.
>> Currently, I am running a very inefficient loop (using a lot of 
>> -levelof-s and if-qualifiers), along these lines (my data is
>> corr x l2.x [aweight=weight] if year==`i' & country==`j', covariance
>> I then write the results [r(cov_12)] into a variable, again using 
>> if-qualifiers.
>> A much quicker way to do this is to use the corr() function (written
> by 
>> Nick Winter) from the egenmore package. It does exactly what I want, 
>> except that it does not accept weights.
>> I can also run something like:
>> bys country year: correlate(x l2.x) [aweight=weight], covariance
>> but r(C) leaves behind the covariance matrix only for the very last 
>> estimation.
>> So, ideally I am looking for a version of Nick Winter's corr() which 
>> accepts weights.
>> Any ideas / suggestions would be appreciated. I prefer a solution
>> works in Stata 9, but I do have access to Stata 10.

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