1 # Buildsheet autogenerated by ravenadm tool -- Do not edit.
7 SDESC[standard]= Robust Covariance Matrix Estimators
9 CONTACT= CRAN_Automaton[cran@ironwolf.systems]
12 SITES[main]= CRAN/src/contrib
13 DISTFILE[1]= sandwich_3.0-1.tar.gz:main
16 SPKGS[standard]= single
18 OPTIONS_AVAILABLE= none
19 OPTIONS_STANDARD= none
21 BUILDRUN_DEPENDS= R-zoo:single:standard
29 INSTALL_REQ_TOOLCHAIN= yes
31 [FILE:1098:descriptions/desc.single]
32 sandwich: Robust Covariance Matrix Estimators
34 Object-oriented software for model-robust covariance matrix estimators.
35 Starting out from the basic robust Eicker-Huber-White sandwich covariance
36 methods include: heteroscedasticity-consistent (HC) covariances for
37 cross-section data; heteroscedasticity- and autocorrelation-consistent
38 (HAC) covariances for time series data (such as Andrews' kernel HAC,
39 Newey-West, and WEAVE estimators); clustered covariances (one-way and
40 multi-way); panel and panel-corrected covariances;
41 outer-product-of-gradients covariances; and (clustered) bootstrap
42 covariances. All methods are applicable to (generalized) linear model
43 objects fitted by lm() and glm() but can also be adapted to other classes
44 through S3 methods. Details can be found in Zeileis et al. (2020) <<a
45 href="https://doi.org/10.18637%2Fjss.v095.i01">doi:10.18637/jss.v095.i01</a>>,
47 href="https://doi.org/10.18637%2Fjss.v011.i10">doi:10.18637/jss.v011.i10</a>>
48 and Zeileis (2006) <<a
49 href="https://doi.org/10.18637%2Fjss.v016.i09">doi:10.18637/jss.v016.i09</a>>.
53 f6584b7084f3223bbc0c4722f53280496be73849747819b0cb4e8f3910284a89 1482805 CRAN/sandwich_3.0-1.tar.gz