The goal of orthoDr is to use an orthogonality
constrained optimization algorithm to solve a variety of dimension
reduction problems in the semiparametric framework.
You can install the released version of orthoDr from CRAN with:
install.packages("orthoDr")This package implements the orthogonality constrained (Stiefel
manifold) optimization approach proposed by Wen
& Yin (2013). A drop-in solver ortho_optim() works
just the same as the optim() function. Relying on this
optimization approach, we also implemented a collection of dimension
reduction models for survival analysis, regression, and personalized
medicine.
We also implemented several methods and functions for comparison, testing and utilization purposes
hMave: This is a direct R translation of
the hMave MATLAB code by Xia,
Zhang & Xu (2010)pSAVE: partial-SAVE in Feng,
Wen, Yu & Zhu (2013)dist_cross(): kernel distances matrix between two sets
of data, as an extension of dist()distance(): distance correlation between two linear
spacessilverman(): Silverman’s rule of thumb bandwidth