sandwich (version 1.9-0)

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. Report 37, Department of Statistics and Mathematics, Wirtschaftsuniversit�t{Wirtschaftsuniversitaet} Wien, Research Report Series. http://epub.wu-wien.ac.at/

See Also

sandwich, bread, estfun

Examples

x <- sin(1:10)
y <- rnorm(10)
fm <- lm(y ~ x)

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