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Last data update: 2014.03.03

R: Method for Profiling glm Objects

profile.glm

R Documentation

Method for Profiling glm Objects

Description

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

Usage

## S3 method for class '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.

Author(s)

Originally, D. M. Bates and W. N. Venables. (For S in 1996.)

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)))
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg <- glm(SF ~ sex*ldose, family = binomial)
pr1 <- profile(budworm.lg)
plot(pr1)
pairs(pr1)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MASS)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MASS/profile.glm.Rd_%03d_medium.png", width=480, height=480)
> ### Name: profile.glm
> ### Title: Method for Profiling glm Objects
> ### Aliases: profile.glm
> ### Keywords: regression models
> 
> ### ** 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)))
> SF <- cbind(numdead, numalive = 20 - numdead)
> budworm.lg <- glm(SF ~ sex*ldose, family = binomial)
> pr1 <- profile(budworm.lg)
> plot(pr1)
> pairs(pr1)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>