RE: st: Calculation of covariance matrix for unbalanced sample?

[Nick Cox <n.j.cox@durham.ac.uk>]

-makematrix- (SJ) can do this. But it's better to use Stas' custom code, which is more direct. 

Nick 
n.j.cox@durham.ac.uk 

Stas Kolenikov

I don't think there's any. I vaguely remember a discussion some time
back on the list about this. Here's the basic outline from scratch:

program define pwcovmat, rclasssyntax varlistunab vars :
`varlist'local p : word count `vars'tempname Covmatrix `Cov' =
J(`p',`p',.)matrix rownames `Cov' = `vars'matrix colnames `Cov' =
`vars'forvalues i=1/`p' {  forvalues j=`i'/`p' {    local x : word `i'
of `vars'    local y : word `j' of `vars'    quietly corr `x' `y', cov
   matrix `Cov'[`i',`j'] = r(C)    matrix `Cov'[`j',`i'] = r(C)
}}return matrix Cov = `Cov'end // of pwcovmat
sysuse auto
corr weight price mpg, cov
corr weight price mpg rep, cov
pwcovmat weight price mpg rep
matrix list r(Cov)

On Thu, Nov 3, 2011 at 6:00 AM,  <S.Jenkins@lse.ac.uk> wrote:

> A colleague has data on a relatively large number of variables. His
> sample is unbalanced in the sense that each variable has some missing
> values. He wishes to calculate the covariance matrix for his data but
> without the listwise deletion of cases that is imposed by -correlation,
> covariance-  or -matrix accum-.
>
> My first thought was that he could use -pwcorr- and loop over his
> variables, and build up his matrix from the saved results. But I thought
> there must be an easier or more straightforward way -- but Googling and
> -findit- have not suggested any.  I guess there is a relatively easy
> Mata solution, but I am currently unfamiliar with that route.
>
> Suggestions using Stata or Mata please

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