pscl (version 0.5)

predprob.glm: Predicted Probabilties for GLM Fits

Description

Obtains predicted probabilities from a fitted generalized linear model object.

Usage

## S3 method for class 'glm':
predprob(obj,newdata=NULL,...)

Arguments

obj

a fitted object of class inheriting from "glm"

newdata

optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used.

...

Value

• 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(min(y):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.

Details

This method is only defined for glm objects with family=binomial or family=poisson, or negative binomial count models fit with the glm.nb function in library(MASS).

See Also

predict.glm

Examples

data(bioChemists)
glm1 <- glm(art ~ .,
            data=bioChemists,
            family=poisson,
            trace=TRUE)  ## poisson GLM
phat <- predprob(glm1)
apply(phat,1,sum)                    ## almost all 1.0