confint                package:stats                R Documentation

Confidence Intervals for Model Parameters

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.

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:

     fit <- lm(100/mpg ~ disp + hp + wt + am, data=mtcars)
     confint(fit)
     confint(fit, "wt")

     ## from example(glm) (needs MASS to be present on the system)
     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)
     confint.default(glm.D93)  # based on asymptotic normality

