meat function

A Simple Meat Matrix Estimator

Estimating the variance of the estimating functions of a regression model by cross products of the empirical estimating functions. UTF-8

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.

Details

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

Returns

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

See Also

sandwich, bread, estfun

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 ofClustered Covariances in R.

Journal of Statistical Software, 95 (1), 1--36. tools:::Rd_expr_doi("10.18637/jss.v095.i01")

Examples

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

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