orthoDr

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) doi:10.1093/biomet/asy064 and Zhou, Zhu & Zeng (2021) doi:10.1093/biomet/asaa087. The package also implements some existing dimension reduction methods such as hMave by Xia, Zhang, & Xu (2010) doi:10.1198/jasa.2009.tm09372 and partial SAVE by Feng, Wen & Zhu (2013) doi:10.1080/01621459.2012.746065. It also serves as a general purpose optimization solver for problems with orthogonality constraints, i.e., in Stiefel manifold. Parallel computing for approximating the gradient is enabled through 'OpenMP'.