orthoDr: semiparametric dimension reduction via orthogonality constrained optimization

11/28/2018

∙

by   Ruoqing Zhu, et al.

∙

0

∙

share

orthoDr is a package in R that solves dimension reduction problems using a 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 Wen & Yin (2013) 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.