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 bandwidthAny scripts or data that you put into this service are public.
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