Have a look at the linear.hypothesis function in the car package. For example:
> mod.duncan <- lm(prestige ~ income + education, data=Duncan) > > linear.hypothesis(mod.duncan, "income + education = 1") Linear hypothesis test Hypothesis: income + education = 1 Model 1: prestige ~ income + education Model 2: restricted model Res.Df RSS Df Sum of Sq F Pr(>F) 1 42 7506.7 2 43 8045.2 -1 -538.5 3.0129 0.08994 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 On 27/09/06, Mesomeris, Spyros [CIR] <[EMAIL PROTECTED]> wrote: > Hello R helpers, > > I am trying to do a linear OLS regression of y on two variables x1 and > x2. I want to constrain the coefficients of x1 and x2 to sum up to 1. > and therefore run a constrained OLS. Can anybody help with this? (I have > seen some answers to similar questions but it was not clear to me what I > need to do) - I have tried the lm function with offset but I must not > have used it properly. > > Thanks, > Spyros > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > -- ================================= David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP ______________________________________________ R-help@stat.math.ethz.ch 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.