sandwich

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.

Last 30 days

This package has been downloaded 232,594 times in the last 30 days. That's a whole lot of downloads. Somewhere, a librarian is trying to figure out why more bandwidth is needed. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7,433 times.

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Last 365 days

This package has been downloaded 2,295,665 times in the last 365 days. Whoa! That's more downloads than an AI-generated meme in a tech-savvy group chat. Truly legendary! The day with the most downloads was Nov 19, 2024 with 10,754 downloads.

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