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r-cran-clubsandwich package

r-cran-clubsandwich 0.3.5-2 source package in Ubuntu

Changelog

r-cran-clubsandwich (0.3.5-2) unstable; urgency=medium

  * Team upload.
  * debhelper-compat 12
  * Standards-Version: 4.4.1
  * Trim trailing whitespace.

 -- Dylan Aïssi <email address hidden>  Sun, 27 Oct 2019 15:56:56 +0100

Upload details

Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Focal: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-clubsandwich_0.3.5-2.dsc 2.1 KiB 6bb0cbaa7496fffd62bd0d60bee3986b850b6f62ab64958273087c9ff639d65b
r-cran-clubsandwich_0.3.5.orig.tar.gz 270.9 KiB 8950c55ddbd3e11b42ef26b0008de9d72ae53e87097f7e747cf11128e076bd0e
r-cran-clubsandwich_0.3.5-2.debian.tar.xz 2.5 KiB 7b29128ede6235efde56b3632ece70c4c51f0b3433d36eb10ceb87a022430d70

Available diffs

No changes file available.

Binary packages built by this source

r-cran-clubsandwich: GNU R cluster-robust (Sandwich) variance estimators with small-sample

 Corrections Provides several cluster-robust variance estimators
 (i.e., sandwich estimators) for ordinary and weighted least
 squares linear regression models, including the bias-reduced
 linearization estimator introduced by Bell and McCaffrey (2002)
 <http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf>
 and developed further by Pustejovsky and Tipton (2017)
 <DOI:10.1080/07350015.2016.1247004>. The package includes
 functions for estimating the variance- covariance matrix and for
 testing single- and multiple- contrast hypotheses based on Wald
 test statistics. Tests of single regression coefficients use
 Satterthwaite or saddle-point corrections. Tests of multiple-contrast
 hypotheses use an approximation to Hotelling's T-squared
 distribution. Methods are provided for a variety of fitted models,
 including lm() and mlm objects, glm(), ivreg() (from package
 'AER'), plm() (from package 'plm'), gls() and lme() (from 'nlme'),
 robu() (from 'robumeta'), and rma.uni() and rma.mv() (from
 'metafor').