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Data sets are often corrupted by outliers. When data are multivariate outliers can be classified as case-wise or cell-wise. The latters are particularly challenge to handle. We implement a robust estimation procedure for Seemingly Unrelated Regression Models which is able to cope well with both type of outliers. Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli (2021) <doi:10.48550/arXiv.2107.00975>.
Version: | 0.0-7 |
Depends: | R (≥ 3.0.0), robustbase, robreg3S |
Imports: | Matrix, GSE |
Suggests: | systemfit |
Published: | 2021-10-04 |
DOI: | 10.32614/CRAN.package.robustsur |
Author: | Claudio Agostinelli [aut, cre], Giovanni Saraceno [aut] |
Maintainer: | Claudio Agostinelli <claudio.agostinelli at unitn.it> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | robustsur results |
Reference manual: | robustsur.pdf |
Package source: | robustsur_0.0-7.tar.gz |
Windows binaries: | r-devel: robustsur_0.0-7.zip, r-release: robustsur_0.0-7.zip, r-oldrel: robustsur_0.0-7.zip |
macOS binaries: | r-release (arm64): robustsur_0.0-7.tgz, r-oldrel (arm64): robustsur_0.0-7.tgz, r-release (x86_64): robustsur_0.0-7.tgz, r-oldrel (x86_64): robustsur_0.0-7.tgz |
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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.