drc (version 1.7-2)

confint.drc: Confidence Intervals for model parameters

Description

Computes confidence intervals for one or more parameters in a model of class 'drc'.

Usage

## S3 method for class 'drc':
confint(object, parm, level = 0.95, type = "t", pool = TRUE, ...)

Arguments

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.

type

the type of confidence interval: based on the standard normal distribution or based on a t-distribution (default).

pool

logical. If TRUE curves are pooled. Otherwise they are not. This argument only works for models with independently fitted curves as specified in drm.

...

additional argument(s) for methods. Not used.

Value

• 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

Details

The confidence intervals are based on asymptotic normality.

Examples

## 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")