sandwich:Robust Covariance Matrix Estimators
Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic robust
Eicker-Huber-White sandwich covariance methods include:
heteroscedasticity-consistent (HC) covariances for
cross-section data; heteroscedasticity- and
autocorrelation-consistent (HAC) covariances for time series
data (such as Andrews' kernel HAC, Newey-West, and WEAVE
estimators); clustered covariances (one-way and multi-way);
panel and panel-corrected covariances;
outer-product-of-gradients covariances; and (clustered)
bootstrap covariances. All methods are applicable to
(generalized) linear model objects fitted by lm() and glm() but
can also be adapted to other classes through S3 methods.
Details can be found in Zeileis et al. (2020)
<doi:10.18637/jss.v095.i01>, Zeileis (2004)
<doi:10.18637/jss.v011.i10> and Zeileis (2006)
<doi:10.18637/jss.v016.i09>.
