I would like to perform a regression like the one below: lm(x ~ 0 + a1 + a2 + a3 + b1 + b2 + b3 + c1 + c2 + c3, data=data)
However, the data has the property that a1+a2+a3 = A, b1+b2+b3 = B, and c1+c2+c3 = C, where A, B, and C are positive constants. So there are two extra degrees of freedom, and R handles this by producing NA for two of the coefficients. Instead, I would prefer to remove the degrees of freedom by forcing constraints on the coefficients produced by the model. Specifically, I want coeff(b1) + coeff(b2) + coeff(b3) = coeff(c1) + coeff(c2) + coeff(c3) = 0. I could accomplish this by writing code to suitably shift the coefficients after performing the basic regression above, but I'm hoping there's a better way. Is there? thanks, Rnewb -- View this message in context: http://www.nabble.com/linear-model-with-coefficient-constraints-tp25769020p25769020.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
