brglm2 (version 0.6.0)

predict.bracl: Predict method for bracl fits

Description

Obtain class and probability predictions from a fitted adjacent category logits model.

Usage

# S3 method for bracl
predict(object, newdata, type = c("class", "probs"), ...)

Arguments

object

a fitted object of class inheriting from "bracl".

newdata

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

type

the type of prediction required. The default is "class", which produces predictions of the response category at the covariate values supplied in "newdata", selecting the category with the largest probability; the alternative "probs" returns all category probabilities at the covariate values supplied in "newdata".

...

further arguments passed to or from other methods.

Value

If type = "class" a vector with the predicted response categories; if type = "probs" a matrix of probabilities for all response categories at newdata.

Details

If newdata is omitted the predictions are based on the data used for the fit.

Examples

# NOT RUN {
data("stemcell", package = "brglm2")

# Adjacent category logit (non-proportional odds)
fit_bracl <- bracl(research ~ as.numeric(religion) + gender, weights = frequency,
                   data = stemcell, type = "ML")
# Adjacent category logit (proportional odds)
fit_bracl_p <- bracl(research ~ as.numeric(religion) + gender, weights = frequency,
                    data = stemcell, type = "ML", parallel = TRUE)

# New data
newdata <- expand.grid(gender = c("male", "female"),
                       religion = c("liberal", "moderate", "fundamentalist"))

# Predictions
sapply(c("class", "probs"), function(what) predict(fit_bracl, newdata, what))
sapply(c("class", "probs"), function(what) predict(fit_bracl_p, newdata, what))

# }