Optimally robust estimation using S4 classes and methods. Old version still needed
for current versions of ROptRegTS and RobRex.

Optimally Robust Estimation - Old Version
person("Matthias", "Kohl", role=c("aut", "cre", "cph"),
email="Matthias.Kohl@stamats.de")

Optimally robust estimation using S4 classes and methods. Old version still
needed for current versions of ROptRegTS and RobRex.

Optimally robust estimation for regression-type models
Optimally robust estimation for regression-type
models using S4 classes and methods

Optimally robust estimation for regression-type models
using S4 classes and methods
Matthias Kohl <Matthias.Kohl@stamats.de>, Peter Ruckdeschel

Optimally robust estimation for regression-type models using S4 classes and
methods

Optimally Robust Estimation for Regression-Type Models
Optimally robust estimation for regression-type models using S4 classes and
methods.
c(person("Matthias", "Kohl", role=c("cre", "aut", "cph"),
email="Matthias.Kohl@stamats.de"), person("Peter", "Ruckdeschel", role=c("aut",
"cph")))
Matthias Kohl [cre, aut, cph],
Peter Ruckdeschel [aut, cph]

R(>= 3.4), methods, ROptEstOld(>= 1.2.0)

Matrix Reconstruction from a Few Entries
Matrix reconstruction, also known as matrix completion, is
the task of inferring missing entries of a partially observed matrix.
This package provides a method called OptSpace,
which was proposed by Keshavan, R.H., Oh, S., and Montanari, A. (2009)
<doi:10.1109/ISIT.2009.5205567> for a case under low-rank assumption.

person("Kisung", "You", role = c("aut", "cre"),email = "kyou@nd.edu",comment=c(ORCID="0000-0002-8584-459X"))

person("Kisung", "You", role = c("aut", "cre"),email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X"))
Matrix reconstruction, also known as matrix completion, is the task of inferring missing entries of a partially observed matrix. This package provides a method called OptSpace, which was proposed by Keshavan, R.H., Oh, S., and Montanari, A. (2009) <doi:10.1109/ISIT.2009.5205567> for a case under low-rank assumption.