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: walmes@ufpr.br
twitter: @walmeszeviani
homepage: http://www.leg.ufpr.br/~walmes
linux user number: 531218
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