profile.glm

0th

Percentile

Method for Profiling glm Objects

Investigates the profile log-likelihood function for a fitted model of class "glm".

Keywords
models, regression
Usage
# S3 method for glm
profile(fitted, which = 1:p, alpha = 0.01, maxsteps = 10,
        del = zmax/5, trace = FALSE, …)
Arguments
fitted
the original fitted model object.
which
the original model parameters which should be profiled. This can be a numeric or character vector. By default, all parameters are profiled.
alpha
highest significance level allowed for the profile t-statistics.
maxsteps
maximum number of points to be used for profiling each parameter.
del
suggested change on the scale of the profile t-statistics. Default value chosen to allow profiling at about 10 parameter values.
trace
logical: should the progress of profiling be reported?
further arguments passed to or from other methods.
Details

The profile t-statistic is defined as the square root of change in sum-of-squares divided by residual standard error with an appropriate sign.

Value

A list of classes "profile.glm" and "profile" with an element for each parameter being profiled. The elements are data-frames with two variables

par.vals
a matrix of parameter values for each fitted model.
tau
the profile t-statistics.

See Also

glm, profile, plot.profile

Aliases
  • profile.glm
Examples
library(MASS) options(contrasts = c("contr.treatment", "contr.poly")) ldose <- rep(0:5, 2) numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16) sex <- factor(rep(c("M", "F"), c(6, 6))) SF <- cbind(numdead, numalive = 20 - numdead) budworm.lg <- glm(SF ~ sex*ldose, family = binomial) pr1 <- profile(budworm.lg) plot(pr1) pairs(pr1)
Documentation reproduced from package MASS, version 7.3-47, License: GPL-2 | GPL-3

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