R: Return the variance-covariance matrix for the regression...

vcov.brglmFit {brglm2} | R Documentation

## Return the variance-covariance matrix for the regression parameters in a `brglmFit` object

### Description

Return the variance-covariance matrix for the regression parameters in a `brglmFit` object

### Usage

    ## S3 method for class 'brglmFit'
    vcov(object, model = c("mean", "full", "dispersion"), complete = TRUE, ...)

### Arguments

`object` | a fitted model object, typically. Sometimes also a `summary()` object of such a fitted model.
`model` | character specifying for which component of the model coefficients should be extracted.
`complete` | for the `aov`, `lm`, `glm`, `mlm`, and where applicable `summary.lm` etc methods: logical indicating if the full variance-covariance matrix should be returned also in case of an over-determined system where some coefficients are undefined and `coef(.)` contains `NA`s correspondingly. When `complete = TRUE`, `vcov()` is compatible with `coef()` also in this singular case.
`...` | additional arguments for method functions. For the `glm` method this can be used to pass a `dispersion` parameter.

### Details

The options for `model` are `"mean"` for mean regression parameters only (default), `"dispersion"` for the dispersion parameter (or the transformed dispersion; see `brglm_control`), and `"mean"` for both the mean regression and the (transformed) dispersion parameters.

[Package brglm2 version 0.6.2 Index]