residuals.glmGamPoi: Extract Residuals of Gamma Poisson Model

In glmGamPoi: Fit a Gamma-Poisson Generalized Linear Model

Description

Extract Residuals of Gamma Poisson Model

Usage

## S3 method for class 'glmGamPoi'
residuals(
  object,
  type = c("deviance", "pearson", "randomized_quantile", "working", "response"),
  ...
)

Arguments

object	a fit of type glmGamPoi. It is usually produced with a call to glm_gp().
type	the type of residual that is calculated. See details for more information. Default: "deviance".
...	currently ignored.

Details

This method can calculate a range of different residuals:

deviance

The deviance for the Gamma-Poisson model is

dev = 2 * (1/theta * log((1 + m * theta) / (1 + y * theta)) - y log((m + y * theta) / (y + y * m * theta)))

and the residual accordingly is

res = sign(y - m) sqrt(dev).

pearson

The Pearson residual is res = (y - m) / sqrt(m + m^2 * theta)

randomized_quantile

The randomized quantile residual was originally developed by Dunn & Smyth, 1995. Please see that publication or statmod::qresiduals() for more information.

working

The working residuals are res = (y - m) / m.

response

The response residuals are res = y - m

Value

a matrix with the same size as fit$data. If fit$data contains a DelayedArray than the result will be a DelayedArray as well.

See Also

glm_gp() and 'stats::residuals.glm()

glmGamPoi documentation built on Nov. 8, 2020, 7:14 p.m.