Confidence Intervals for model parameters
Computes confidence intervals for one or more parameters in a model of class 'drc'.
## S3 method for class 'drc' confint(object, parm, level = 0.95, pool = TRUE, ...)
object |
a model object of class 'drc'. |
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. |
level |
the confidence level required. |
pool |
logical. If TRUE curves are pooled. Otherwise they are not. This argument only works for models with
independently fitted curves as specified in |
... |
additional argument(s) for methods. Not used. |
For binomial and Poisson data the confidence intervals are based on the normal distribution, whereas t distributions are used of for continuous/quantitative data.
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in
Christian Ritz
## Fitting a four-parameter log-logistic model ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = LL.4()) ## Confidence intervals for all parameters confint(ryegrass.m1) ## Confidence interval for a single parameter confint(ryegrass.m1, "e")
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