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Re: st: simple matrix calculations


From   Mark Schaffer <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu, Stuart Jordan <sjordan@Princeton.EDU>
Subject   Re: st: simple matrix calculations
Date   Wed, 05 Feb 2003 00:11:29 +0000 (GMT)

You want to use matrix accumulate.  If X is n by k1, and Z is n by k2, then

mat accum XZ = X Z, nocons

(assuming that you already have or don't need a constant column)

results in the (k1+k2) by (k1+k2) cross-product matrix called XZ.  The 
upper-left-hand k1 by k1 block of XZ is X'X, the lower-right-hand k2 by k2 
block of XZ is Z'Z, and the off-diagonal blocks (k1 by k2 and k2 by k1) are 
X'Z and Z'X.

Hope this is what you are looking for....

--Mark

Quoting Stuart Jordan <sjordan@Princeton.EDU>:

> I am trying to find a simple way to compute X'Z in stata where X is
> an n
> by k matrix, and Z is an n by l matrix with k>=l, and where these
> matrices are made up of columns of observations from my dataset. 
> The
> stata programming manual makes it sound as if this should be
> straightfoward using one of the matrix accum commands...but the
> only
> ways I've been able to figure out how to do it with these commands
> require a burdensome amount of complicated code.
> 
> I'm not able to do this using the mkmat command because my dataset
> is
> too large given stata 8's maximum matsize of 800.
> 
> In case it matters, the application I want to use this for is to
> compute
> X'Z where X is a matrix of observations on a set of exogenous
> regressors
> and instruments and Z is a matrix of observation on a set of the
> same
> exogenous regressors and a set of endogenous regressors.
> 
> Even though I could do this in Matlab or Gauss easily, I use stata
> more
> often, so would like to learn how to do it there.
> 
> Thanks,
> 
> Stu Jordan
> 
> *
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> 



Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3008
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes
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