c(person(given = "Marc", family = "Hofmann",
role  = c("aut", "cre"),
email = "marc.hofmann@gmail.com"),
person(given = "Cristian", family = "Gatu",
role  = "aut",
email = "cgatu@info.uaic.ro"),
person(given = "Erricos J.", family = "Kontoghiorghes",
role = "aut",
email = "erricos@dcs.bbk.ac.uk"),
person(given = "Achim", family = "Zeileis",
role = "aut",
email = "Achim.Zeileis@R-project.org",
comment = c(ORCID = "0000-0003-0918-3766")),
person(given = "Martin", family = "Moene",
role = "cph",
comment = "for the GSL Lite library"),
person(given = "Microsoft Corporation",
role = "cph",
comment = "for the GSL Lite library"),
person(given = "Free Software Foundation, Inc.",
role = "cph",
comment = "for snippets from the GNU ISO C++ Library"))
Marc Hofmann [aut, cre],
Cristian Gatu [aut],
Erricos J. Kontoghiorghes [aut],
Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>),
Martin Moene [cph] (for the GSL Lite library),
Microsoft Corporation [cph] (for the GSL Lite library),
Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++
Library)

c(person(given = "Marc", family = "Hofmann",
role  = c("aut", "cre"),
email = "marc.hofmann@gmail.com"),
person(given = "Cristian", family = "Gatu",
role  = "aut",
email = "cgatu@info.uaic.ro"),
person(given = "Erricos J.", family = "Kontoghiorghes",
role = "aut",
email = "erricos@dcs.bbk.ac.uk"),
person(given = "Ana", family = "Colubi",
role = "aut",
email = "ana.colubi@gmail.com"),
person(given = "Achim", family = "Zeileis",
role = "aut",
email = "Achim.Zeileis@R-project.org",
comment = c(ORCID = "0000-0003-0918-3766")),
person(given = "Martin", family = "Moene",
role = "cph",
comment = "for the GSL Lite library"),
person(given = "Microsoft Corporation",
role = "cph",
comment = "for the GSL Lite library"),
person(given = "Free Software Foundation, Inc.",
role = "cph",
comment = "for snippets from the GNU ISO C++ Library"))
Exact and approximation algorithms for variable-subset
selection in ordinary linear regression models.  Either compute all
submodels with the lowest residual sum of squares, or determine the
single-best submodel according to a pre-determined statistical
criterion.  Hofmann, Gatu, Kontoghiorghes, Colubi, Zeileis (2018,
submitted).
Marc Hofmann [aut, cre],
Cristian Gatu [aut],
Erricos J. Kontoghiorghes [aut],
Ana Colubi [aut],
Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>),
Martin Moene [cph] (for the GSL Lite library),
Microsoft Corporation [cph] (for the GSL Lite library),
Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++
Library)