Confidence Intervals for Model Parameters

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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

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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 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

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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 installed
confint.default(glm.D93)  # based on asymptotic normality

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