In article <[EMAIL PROTECTED]>,
Arie Beresteanu <[EMAIL PROTECTED]> wrote:
>Hi,
> Estimation of linear (multivariate) regression with equality constrains
>on the coefficients is a well known problem (at least for me). What
>about if the constrains are inequalities? More specifically:
>Y=Xb+e
>s.t.
>Qb<=q
>where Q is a matrix and q is a vector. (for example Y=b0+b1*X1+b2*X2+e
>s.t. b1+2*b2>=0 )
>How do I solve that? How do I test the constrain? Is there something on
>MatLab/STATA/SAS for that?
The general theory for optimization of anything subject to
inequality constraints is that each inequality is ineffective
or is exact. One can do better for finding a solution by
the use of directional derivatives.
The problem here is a problem of quadratic programming, about
which there is considerable literature.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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