meat

0th

Percentile

A Simple Meat Matrix Estimator

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

Keywords
regression
Usage
meat(x, adjust = FALSE, …)
Arguments
x

a fitted model object.

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 $$k \times k$$ 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. URL http://www.jstatsoft.org/v16/i09/.

sandwich, bread, estfun
library(sandwich) # NOT RUN { x <- sin(1:10) y <- rnorm(10) fm <- lm(y ~ x) meat(fm) meatHC(fm, type = "HC") meatHAC(fm) # }