Utilize an orthogonality constrained optimization algorithm of
Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of
dimension reduction problems in the semiparametric framework, such as
Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013)
<DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2017) <arXiv:1704.05046>
and Zhou & Zhu (2018+) <arXiv:1802.06156>. It also serves as a general
purpose optimization solver for problems with orthogonality constraints.
Parallel computing for approximating the gradient is enabled
through `OpenMP'.

c(
person("Ruilin", "Zhao",
email = "rzhao15@seas.upenn.edu",
role = c("aut", "cph")),
person("Ruoqing", "Zhu",
email = "teazrq@gmail.com",
role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-0753-5716")),
person("Jiyang", "Zhang",
email = "jiyangz2@illinois.edu",
role = c("aut", "cph")),
person("Wenzhuo", "Zhou",
email = "wenzhuo3@illinois.edu",
role = c("aut", "cph")),
person("Peng", "Xu",
email = "px2132@columbia.edu",
role = c("aut", "cph")),
person("James Joseph", "Balamuta",
email = "balamut2@illinois.edu",
role = c("ctb"),
comment = c(ORCID = "0000-0003-2826-8458"))
)
Utilize an orthogonality constrained optimization algorithm of
Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of
dimension reduction problems in the semiparametric framework, such as
Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013)
<DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2019) <arXiv:1704.05046>
and Zhou, Zhu & Zeng (2021) <arXiv:1802.06156>. It also serves as a general
purpose optimization solver for problems with orthogonality constraints.
Parallel computing for approximating the gradient is enabled
through 'OpenMP'.
Rcpp (>= 1.0.9), survival, dr, pracma, plot3D, rgl, MASS
Ruilin Zhao [aut, cph],
Ruoqing Zhu [aut, cre, cph] (<https://orcid.org/0000-0002-0753-5716>),
Jiyang Zhang [aut, cph],
Wenzhuo Zhou [aut, cph],
Peng Xu [aut, cph],
James Joseph Balamuta [ctb] (<https://orcid.org/0000-0003-2826-8458>)