bergrm-methods: Methods for 'bergrm' objects

In rdmatheus/bergrm: BerG Regression Model for Count Data

Description

Methods for 'bergrm' objects

Usage

## S3 method for class 'bergrm'
plot(x, residual = c("all", "quantile", "pearson"), ...)

## S3 method for class 'bergrm'
logLik(object, ...)

## S3 method for class 'bergrm'
AIC(object, ..., k = 2)

## S3 method for class 'bergrm'
coef(object, what = c("all", "mean", "dispersion"), ...)

## S3 method for class 'bergrm'
vcov(object, ...)

## S3 method for class 'bergrm'
model.matrix(object, matrix = c("all", "mean", "dispersion"), ...)

Arguments

residual	character; specifies which residual should be produced in the summary plot. The available arguments are "all" for both randomized quantile and Pearson residuals; "quantile" for randomized quantile residuals; and "pearson" for Pearson residuals.
...	further additional arguments.
object	an object of class bergrm.
k	numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.
what	a character indicating which parameter coefficients are required, parameters for the "mean" or for the "dispersion" model. If "all" (default), a list with coefficients for the mean and for the dispersion model is returned.
matrix	a character indicating which model matrix is required, the model matrix for the mean ("mean") or for the dispersion parameter ("dispersion"). If "all" (default), a list with with both matrices are returned.

Value

.

Author(s)

Rodrigo M. R. Medeiros <[e-mail]>

References

Bourguignon, M. and Medeiros, R. M. R. (2020). A simple and useful regression model for fitting count data.

rdmatheus/bergrm documentation built on Oct. 1, 2020, 4:38 a.m.