sandwich: meat – R documentation

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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.

Details

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

Value

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

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

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

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

sandwich

Robust Covariance Matrix Estimators

v3.0-0

GPL-2 | GPL-3

Authors

Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Thomas Lumley [aut], Nathaniel Graham [ctb], Susanne Koell [ctb]

Initial release

2020-10-01