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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>.
Version: | 3.1-1 |
Depends: | R (≥ 3.0.0) |
Imports: | stats, utils, zoo |
Suggests: | AER, car, geepack, lattice, lme4, lmtest, MASS, multiwayvcov, parallel, pcse, plm, pscl, scatterplot3d, stats4, strucchange, survival |
Published: | 2024-09-15 |
DOI: | 10.32614/CRAN.package.sandwich |
Author: | Achim Zeileis [aut, cre], Thomas Lumley [aut], Nathaniel Graham [ctb], Susanne Koell [ctb] |
Maintainer: | Achim Zeileis <Achim.Zeileis at R-project.org> |
BugReports: | https://sandwich.R-Forge.R-project.org/contact.html |
License: | GPL-2 | GPL-3 |
URL: | https://sandwich.R-Forge.R-project.org/ |
NeedsCompilation: | no |
Citation: | sandwich citation info |
Materials: | README NEWS |
In views: | Econometrics, Finance, Robust |
CRAN checks: | sandwich results |
Package source: | sandwich_3.1-1.tar.gz |
Windows binaries: | r-devel: sandwich_3.1-1.zip, r-release: sandwich_3.1-1.zip, r-oldrel: sandwich_3.1-1.zip |
macOS binaries: | r-release (arm64): sandwich_3.1-1.tgz, r-oldrel (arm64): sandwich_3.1-1.tgz, r-release (x86_64): sandwich_3.1-1.tgz, r-oldrel (x86_64): sandwich_3.1-1.tgz |
Old sources: | sandwich archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.