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.
- Version3.1-1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- sandwich citation info
- Last release09/15/2024
Documentation
- VignetteVarious Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R
- VignetteObject-Oriented Computation of Sandwich Estimators
- VignetteEconometric Computing with HC and HAC Covariance Matrix Estimators
- MaterialREADME
- MaterialNEWS
- In ViewsEconometrics
- In ViewsFinance
- In ViewsRobust
Team
Achim Zeileis
MaintainerShow author detailsThomas Lumley
Show author detailsRolesAuthorNathaniel Graham
Show author detailsRolesContributorSusanne Koell
Show author detailsRolesContributor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Suggests14 packages
- Reverse Depends23 packages
- Reverse Imports133 packages
- Reverse Suggests58 packages