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

bread(x, ...)

Arguments

x

a fitted model object.

...

arguments passed to methods.

Value

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.

See also

References

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

Examples

## 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
solve(crossprod(cbind(1, x))) * 10
#> x #> 1.0414689 -0.2938577 #> x -0.2938577 2.0823419