residuals.glmGamPoi {glmGamPoi} | R Documentation

## Extract Residuals of Gamma Poisson Model

### Description

Extract Residuals of Gamma Poisson Model

### Usage

    ## S3 method for class 'glmGamPoi'
    residuals(
      object,
      Y,
      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()`.
`Y` | any matrix-like object (e.g. `matrix()`, `DelayedArray()`, `HDF5Matrix()`) with one column per sample and row per gene.
`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 `Y`. If `Y` is a `DelayedArray` than the result will be as well.

### See Also

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

[Package glmGamPoi version 1.0.0 Index]