predict.BinaryEPPM: Prediction Method for BinaryEPPM Objects

In BinaryEPPM: Mean and Variance Modeling of Binary Data

Description

Extract various types of predictions from BinaryEPPM regression models.

Usage

## S3 method for class 'BinaryEPPM'
predict(object, newdata = NULL, type = c("response", 
     "linear.predictor.p", "linear.predictor.scale.factor",
 "p", "scale.factor", "scale.factor.limits", "mean", 
 "variance",   "distribution", "distribution.parameters"), na.action = na.pass, ...)

Arguments

object	fitted model object of class "BinaryEPPM".
newdata	optionally, a data frame in which to look for variables with which to predict. If omitted, the original observations are used.
type	character indicating type of predictions: fitted means of responses ("response"), linear predictors ("linear.predictor.p", "linear.predictor.scale.factor"), fitted value of probability of success ("p"), fitted value of scale-factor ("scale.factor"), fitted value of mean ("mean"), scale factor limits ("scale.factor.limits"), fitted value of variance ("variance"), fitted probability distribution ("distribution"), parameters of fitted distributions ("distribution.parameters")
na.action	function determining what should be done with missing values in newdata. The default is to predict NA.
...	some methods for this generic function require additional arguments.

Value

A vector or list of the predicted values from the fitted model object.

Author(s)

David M. Smith <[e-mail]>

References

Cribari-Neto F, Zeileis A. (2010). Beta Regression in R. Journal of Statistical Software, 34(2), 1-24. doi: 10.18637/jss.v034.i02.

See Also

predict.betareg

Examples

data("ropespores.case")
output.fn <- BinaryEPPM(data = ropespores.case,
                  number.spores / number.tested ~ 1 + offset(logdilution),
                  model.type = 'p only', model.name = 'binomial')                 
predict(output.fn, type = "response")
predict(output.fn, type = "linear.predictor.p")

BinaryEPPM documentation built on July 31, 2019, 5:08 p.m.