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sandwich (version 3.1-1)

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, ...)

Value

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

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.

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. tools:::Rd_expr_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. tools:::Rd_expr_doi("10.18637/jss.v095.i01")

See Also

sandwich, bread, estfun

Examples

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

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

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