You can also run two nls() models, one under h0 restriction, other under no restriction or h1, and compare them (if they are nested) by likelihood ratio test using anova() method, look
x1 <- seq(0,10,l=15) x2 <- runif(x1) set.seed(1) y <- x1+0.5*x2+rnorm(x1,0,0.01) nls.h0 <- nls(y~b0+x1+b2*x2, start=c(b0=1, b2=1)) nls.h1 <- nls(y~b0+b1*x1+b2*x2, start=c(b0=1, b1=1, b2=1)) summary(nls.h1) anova(nls.h0, nls.h1) another option is to adjust a model parametrized according to test h0, like nls.h2 <- nls(y~b0+(b1+1)*x1+b2*x2, start=c(b0=1, b1=-1, b2=1)) summary(nls.h2) Bests. Walmes ========================================================================== Walmes Marques Zeviani LEG (Laboratório de Estatística e Geoinformação, 25.450418 S, 49.231759 W) Departamento de Estatística - Universidade Federal do Paraná fone: (+55) 41 3361 3573 VoIP: (3361 3600) 1053 1173 e-mail: wal...@ufpr.br twitter: @walmeszeviani homepage: http://www.leg.ufpr.br/~walmes linux user number: 531218 ========================================================================== [[alternative HTML version deleted]]
______________________________________________ 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.
