Semi-Parametric Dimension Reduction Models Using Orthogonality
Utilize an orthogonality constrained optimization algorithm of
Wen & Yin (2013) <10.1007> to solve a variety of
dimension reduction problems in the semiparametric framework, such as
Ma & Zhu (2012) <10.1080>, Ma & Zhu (2013)
<10.1214>, Sun, Zhu, Wang & Zeng (2017) <1704.05046>
and Zhou & Zhu (2018+) <1802.06156>. It also serves as a general
purpose optimization solver for problems with orthogonality constraints.
Parallel computing for approximating the gradient is enabled
Added an experimental version of the semi-direct learning of personalized medicine
model. Also added the efficient estimation procedure of Ma and Zhu (2013).
This is the first release of this package on CRAN.