[R] regression constraints?

[John P. Burkett]

A Bayesian approach to regression with inequality constraints on 
coefficients is to first estimate the regression without constraints, 
then sample from the distribution of the coefficients, discarding all 
draws that violate the constraints, and finally calculate summary 
statistics from the subsample that is consistent with the constraints.  
Andrew Gelman et al. explain how to do that in their Bayesian Data 
Analysis.  I believe they implemented their procedures in S-Plus.  If 
any one has written similar programs in R, I would like very much to 
hear them.

Adam Gehr wrote:

> 
> "Strumila, John" wrote:
> 
>> gday R gurus,
>> 
>> I have a multivariate regression for which I want to constrain the
>> coefficients to be > 0.  Is this possible?
>> 
>> I've check the doco and searched CRAN but can't find anything.
>> 
>> thanks,
>> John Strumila
> 
> 
> I've been doing something like that (regression coefficients
> constrained 
> to be > 0 and also forced to sum to 1) using the quadratic
> programming program solve.QP in package quadprog. 
> 
>     Adam Gehr
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-- 
John P. Burkett
Department of Economics
University of Rhode Island
10 Chafee Road, Suite 3
Kingston, RI 02881-0808

phone (401) 874-4122
fax   (401) 874-2858

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