## Fitting 4-parameter log-logistic model
ryegrass.m1 <- drm(ryegrass, fct = LL.4())
## Calculating EC/ED values
ED(ryegrass.m1, c(10, 50, 90))
## first column: the estimates of ED10, ED50 and ED90
## second column: the corresponding estimated standard errors
### How to use the argument 'ci'
## Also displaying 95% confidence intervals
ED(ryegrass.m1, c(10, 50, 90), interval = "delta")
## Comparing delta method and back-transformed
## confidence intervals for ED values
## Fitting 4-parameter log-logistic
## in different parameterisation (using LL2.4)
ryegrass.m2 <- drm(ryegrass, fct = LL2.4())
ED(ryegrass.m1, c(10, 50, 90), interval = "fls")
ED(ryegrass.m2, c(10, 50, 90), interval = "delta")
### How to use the argument 'bound'
## Fitting the Brain-Cousens model
lettuce.m1 <- drm(weight ~ conc,
data = lettuce, fct = BC.4())
### Calculating ED[-10]
# This does not work
#ED(lettuce.m1, -10)
## Now it does work
ED(lettuce.m1, -10, bound = FALSE) # works
ED(lettuce.m1, -20, bound = FALSE) # works
## The following does not work for another reason: ED[-30] does not exist
#ED(lettuce.m1, -30, bound = FALSE)
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