predict.cmpreg: Predict method for COM-Poisson models

In JrEduardo/cmpreg: Reparametrized COM-Poisson Regression Models

Description

Predict method for COM-Poisson models

Usage

## S3 method for class 'cmpreg'
predict(object, newdata, newmatrices = NULL,
  what = c("mean", "dispersion", "all"), type = c("link", "response"),
  se.fit = FALSE, augment_data = FALSE, ...)

Arguments

object	a fitted object of class 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.
newmatrices	optionally, a list with named design matrices ("X" for mean model and "Z" for dispersion model) used to predict. If omitted, the fitted linear predictors are used.
what	a character indicating which parameter coefficient is required, parameters for the "mean" or for the "dispersion" model.
type	the type of prediction required. The default "link" is on the scale of the linear predictors; the alternative "response" is on the scale of the response variable.
se.fit	logical switch indicating if standard errors are required. Default is FALSE.
augment_data	logical indicating if newdata should be augmented with the predict values and, possibly, standard errors. Default is FALSE.
...	currently not used.

Value

a tibble with fitted values (codefit) and, possibly, standard erros (ste). If augment_data, the result will be the newdata with new columns fit, fitted values, and codeste, standard errors.

Author(s)

Eduardo Jr <[e-mail]>

JrEduardo/cmpreg documentation built on May 8, 2019, 4:41 p.m.