Data are from an experiment, comparing the potency of the two herbicides glyphosate and bentazone in white mustard Sinapis alba.
A data frame with 68 observations on the following 3 variables.
a numeric vector containing the dose in g/ha.
a factor with levels
Glyphosate (the two herbicides applied).
a numeric vector containing the response (dry matter in g/pot).
The lower and upper limits for the two herbicides can be assumed identical, whereas slopes and ED50 values are different (in the log-logistic model).
Christensen, M. G. and Teicher, H. B., and Streibig, J. C. (2003) Linking fluorescence induction curve and biomass in herbicide screening, Pest Management Science, 59, 1303–1310.
See the examples sections for
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## Fitting a log-logistic model with ## common lower and upper limits S.alba.LL.4.1 <- drm(DryMatter~Dose, Herbicide, data=S.alba, fct = LL.4(), pmodels=data.frame(Herbicide,1,1,Herbicide)) summary(S.alba.LL.4.1) ## Applying the optimal transform-both-sides Box-Cox transformation ## (using the initial model fit) S.alba.LL.4.2 <- boxcox(S.alba.LL.4.1, method = "anova") summary(S.alba.LL.4.2) ## Plotting fitted regression curves together with the data plot(S.alba.LL.4.2)