R (>= 2.6.0), MASS, lattice, robustbase, rrcov

Jiahui Wang,
Ruben Zamar <ruben@stat.ubc.ca>,
Alfio Marazzi <Alfio.Marazzi@inst.hospvd.ch>,
Victor Yohai <vyohai@dm.uba.ar>,
Matias Salibian-Barrera <matias@stat.ubc.ca>,
Ricardo Maronna <maron@mate.unlp.edu.ar>,
Eric Zivot <ezivot@u.washington.edu>,
David Rocke <dmrocke@ucdavis.edu>,
Doug Martin <doug@statsci.com>,
Kjell Konis <kjell.konis@epfl.ch>.

Jiahui Wang, Ruben Zamar <ruben@stat.ubc.ca>, Alfio Marazzi
<Alfio.Marazzi@inst.hospvd.ch>, Victor Yohai
<vyohai@dm.uba.ar>, Matias Salibian-Barrera
<matias@stat.ubc.ca>, Ricardo Maronna <maron@mate.unlp.edu.ar>,
Eric Zivot <ezivot@u.washington.edu>, David Rocke
<dmrocke@ucdavis.edu>, Doug Martin, Martin Maechler
<maechler@stat.math.ethz.ch>, Kjell Konis <kjell.konis@me.com>.
R (>= 2.15.0), fit.models, MASS, lattice, robustbase, rrcov

Jiahui Wang, Ruben Zamar <ruben@stat.ubc.ca>, Alfio Marazzi
<Alfio.Marazzi@inst.hospvd.ch>, Victor Yohai
<vyohai@dm.uba.ar>, Matias Salibian-Barrera
<matias@stat.ubc.ca>, Ricardo Maronna <maron@mate.unlp.edu.ar>,
Eric Zivot <ezivot@u.washington.edu>, David Rocke
<dmrocke@ucdavis.edu>, Doug Martin, Martin Maechler
<maechler@stat.math.ethz.ch>, Kjell Konis
<kjell.konis@icloud.com>.

Jiahui Wang,
Ruben Zamar <ruben@stat.ubc.ca>,
Alfio Marazzi <Alfio.Marazzi@inst.hospvd.ch>,
Victor Yohai <vyohai@dm.uba.ar>,
Matias Salibian-Barrera <matias@stat.ubc.ca>,
Ricardo Maronna <maron@mate.unlp.edu.ar>,
Eric Zivot <ezivot@u.washington.edu>,
David Rocke <dmrocke@ucdavis.edu>,
Doug Martin,
Martin Maechler <maechler@stat.math.ethz.ch>,
Kjell Konis <kjell.konis@me.com>.
fit.models, MASS, lattice, robustbase, rrcov, stats

Methods for robust statistics, a state of the art in the early
2000s, notably for robust regression and robust multivariate analysis.
graphics, stats, utils, lattice, MASS, robustbase, rrcov

Orphaned and corrected on 2019-07-02 as installation
issues were not addressed.

LTO

Outlier Robust Two-Stage Least Squares Inference and Testing
person("Jonas", "Kurle", email = "mail@jonaskurle.com",
role = c("aut","cre"), comment = (ORCID = "0000-0003-2197-2012"))
An implementation of easy tools for outlier robust inference in
two-stage least squares (2SLS) models. The user specifies a reference
distribution against which observations are classified as outliers or not.
After removing the outliers, adjusted standard errors are automatically
provided. Furthermore, several statistical tests for the false outlier
detection rate can be calculated. The outlier removing algorithm can be
iterated a fixed number of times or until the procedure converges. The
algorithms and robust inference are described in more detail in Jiao (2019)
<https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view>.
datasets, doFuture, doParallel, future, ggplot2, grDevices,
knitr, MASS, parallel, rmarkdown, testthat, utils