Predicted Probabilities for GLM Fits
Obtains predicted probabilities from a fitted generalized linear model object.
## S3 method for class 'glm' predprob(obj, newdata = NULL, at = NULL, ...)
obj |
a fitted object of class inheriting from |
newdata |
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used. |
at |
an optional numeric vector at which the probabilities are
evaluated. By default |
... |
arguments passed to or from other methods |
A matrix of predicted probabilities. Each row in the matrix is a
vector of probabilities, assigning predicted probabilities over the range of
responses actually observed in the data. For instance, for models
with family=binomial, the matrix has two columns for the "zero"
(or failure) and "one" (success) outcomes, respectively, and
trivially, each row in the matrix sums to 1.0.
For counts fit with family=poisson or via glm.nb, the
matrix has length(0:max(y)) columns. Each observation
used in fitting the model generates a row to the returned matrix; alternatively, if
newdata is supplied, the returned matrix will have as many rows
as in newdata.
Simon Jackman simon.jackman@sydney.edu.au
data(bioChemists)
glm1 <- glm(art ~ .,
data=bioChemists,
family=poisson,
trace=TRUE) ## poisson GLM
phat <- predprob(glm1)
apply(phat,1,sum) ## almost all 1.0Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.