`bread.Rd`

Generic function for extracting an estimator for the bread of sandwiches.

bread(x, ...)

x | a fitted model object. |
---|---|

... | arguments passed to methods. |

A matrix containing an estimator for the expectation of the negative
derivative of the estimating functions, usually the Hessian.
Typically, this should be an \(k \times k\) matrix corresponding
to \(k\) parameters. The rows and columns should be named
as in `coef`

or `terms`

, respectively.

The default method tries to extract `vcov`

and `nobs`

and simply computes their product.

Zeileis A (2006).
“Object-Oriented Computation of Sandwich Estimators.”
*Journal of Statistical Software*, **16**(9), 1--16.
doi: 10.18637/jss.v016.i09

Zeileis A, Köll S, Graham N (2020).
“Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R.”
*Journal of Statistical Software*, **95**(1), 1--36.
doi: 10.18637/jss.v095.i01

## linear regression x <- sin(1:10) y <- rnorm(10) fm <- lm(y ~ x) ## bread: n * (x'x)^{-1} bread(fm)#> (Intercept) x #> (Intercept) 1.0414689 -0.2938577 #> x -0.2938577 2.0823419#> x #> 1.0414689 -0.2938577 #> x -0.2938577 2.0823419