confint
Confidence Intervals for Model Parameters
Computes confidence intervals for one or more parameters in a fitted
model. There is a default and a method for objects inheriting from class
"lm".
- Keywords
- models
Usage
confint(object, parm, level = 0.95, …)Arguments
- object
a fitted model object.
- 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.
- …
additional argument(s) for methods.
Details
confint is a generic function. The default method assumes
normality, and needs suitable coef and
vcov methods to be available. The default method can be
called directly for comparison with other methods.
For objects of class "lm" the direct formulae based on \(t\)
values are used.
There are stub methods in package stats for classes "glm"
and "nls" which call those in package MASS (if
installed): if the MASS namespace has been loaded, its
methods will be used directly. (Those methods are based on profile
likelihood.)
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 % (by default 2.5% and 97.5%).
See Also
confint.glm and
confint.nls in package MASS.
Examples
library(stats)
# NOT RUN {
fit <- lm(100/mpg ~ disp + hp + wt + am, data = mtcars)
confint(fit)
confint(fit, "wt")
# }
# NOT RUN {
## from example(glm)
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3, 1, 9); treatment <- gl(3, 3)
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
confint(glm.D93) # needs MASS to be installed
confint.default(glm.D93) # based on asymptotic normality
# }