# 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 class 'glm':
profile(fitted, which = 1:p, alpha = 0.01, maxsteps = 10,
del = zmax/5, trace = FALSE, \dots)
##### 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.valsa matrix of parameter values for each fitted model.
• tauthe profile t-statistics.

glm, profile, plot.profile

• profile.glm
##### Examples
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)))
pairs(pr1)