orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization
Abstract
orthoDr is a package in R that solves dimension reduction problems using orthogonality constrained optimization approach. The package serves as a unified framework for many regression and survival analysis dimension reduction models that utilize semiparametric estimating equations. The main computational machinery of orthoDr is a first-order algorithm developed by \cite{wen2013feasible} for optimization within the Stiefel manifold. We implement the algorithm through Rcpp and OpenMP for fast computation. In addition, we developed a general-purpose solver for such constrained problems with user-specified objective functions, which works as a drop-in version of optim(). The package also serves as a platform for future methodology developments along this line of work.
Cite
@article{arxiv.1811.11733,
title = {orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization},
author = {Ruoqing Zhu and Jiyang Zhang and Ruilin Zhao and Peng Xu and Wenzhuo Zhou and Xin Zhang},
journal= {arXiv preprint arXiv:1811.11733},
year = {2019}
}