Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) tools:::Rd_expr_doi("10.1007/s10107-012-0584-1") to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) tools:::Rd_expr_doi("10.1080/01621459.2011.646925"), Ma & Zhu (2013) tools:::Rd_expr_doi("10.1214/12-AOS1072"), Sun, Zhu, Wang & Zeng (2019) tools:::Rd_expr_doi("10.1093/biomet/asy064") and Zhou, Zhu & Zeng (2021) tools:::Rd_expr_doi("10.1093/biomet/asaa087"). The package also implements some existing dimension reduction methods such as hMave by Xia, Zhang, & Xu (2010) tools:::Rd_expr_doi("10.1198/jasa.2009.tm09372") and partial SAVE by Feng, Wen & Zhu (2013) tools:::Rd_expr_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'.
Maintainer: Ruoqing Zhu teazrq@gmail.com (ORCID) [copyright holder]
Authors:
Ruilin Zhao rzhao15@seas.upenn.edu [copyright holder]
Jiyang Zhang jiyangz2@illinois.edu [copyright holder]
Wenzhuo Zhou wenzhuo3@illinois.edu [copyright holder]
Peng Xu px2132@columbia.edu [copyright holder]
Other contributors:
James Joseph Balamuta balamut2@illinois.edu (ORCID) [contributor]
Useful links: