regression constraints?
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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