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confint {stats}

Confidence Intervals for Model Parameters
Package: 
stats
Version: 
R 3.0.2

Description

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".

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 asymptotic 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 for classes "glm" and "nls" which invoke those in package MASS which are based on profile likelihoods.

Values

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

fit <- lm(100/mpg ~ disp + hp + wt + am, data = mtcars)
confint(fit)
confint(fit, "wt")
 
## 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 present on the system
confint.default(glm.D93)  # based on asymptotic normality

Documentation reproduced from R 3.0.2. License: GPL-2.