sandwich (version 3.0-0)

meat: A Simple Meat Matrix Estimator

Description

Estimating the variance of the estimating functions of a regression model by cross products of the empirical estimating functions.

Usage

meat(x, adjust = FALSE, …)

Arguments

x

a fitted model object.

adjust

logical. Should a finite sample adjustment be made? This amounts to multiplication with $n/(n-k)$ where $n$ is the number of observations and $k$ the number of estimated parameters.

…

arguments passed to the estfun function.

Value

A $k\times k$ matrix corresponding containing the scaled cross products of the empirical estimating functions.

Details

For some theoretical background along with implementation details see Zeileis (2006).

References

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

Zeileis A, K<U+00F6>ll S, Graham N (2020). “Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R.” Journal of Statistical Software, 95(1), 1--36. 10.18637/jss.v095.i01

See Also

sandwich, bread, estfun

Examples

# NOT RUN {
x <- sin(1:10)
y <- rnorm(10)
fm <- lm(y ~ x)

meat(fm)
meatHC(fm, type = "HC")
meatHAC(fm)
# }