Le mardi 26 mai 2009 à 14:11 -0400, Stu @ AGS a écrit : > Hi! > I am a bit new to R. > I am looking for the right function to use for a multiple regression problem > of the form: > > y = c1 + x1 + (c2 * x2) - (c3 * x3) > > Where c1, c2, and c3 are the desired regression coefficients that are > subject to the following constraints: > > 0.0 < c2 < 1.0, and > 0.0 < c3 < 1.0
Sounds rather like an in-the-closet Bayesian problem (with a very strange prior...). Did you consider to submit it to WinBUGS (or JAGS) ? If you still want a direct optimization, you could have started : RSiteSearch("optimization constraint") Which would have quickly led you to ask : ? constrOptim > y, x1, x2, and x3 are observed data. > I have a total of 6 rows of data in a data set. ??? I that's real-life data, I wonder what kind of situation forces you to estimate 3+1 parameters (c1, c2, c3 and the residual, which is not really a parameter) with 6 data points ? Your problem can be written as a system of 6 linear equations with 3 unknowns (c1, c2, c3), leaving you room to search in (a small piece of) R^3 (the residual is another way to express your objective function, not an independent parameter). Of course, if it's homework, get lost ! Emmanuel Charpentier > Is "optim" in the stats package the right function to use? > Also, I can't quite figure out how to specify the constraints. > Thank you! > > -Stu > ______________________________________________ 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.