Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Kofi Placid Adragni, R. Dennis Cook, Seongho Wu
Title: GrassmannOptim: An R Package for Grassmann Manifold Optimization
Abstract: The optimization of a real-valued objective function f(U), where U is a p X d,p > d, semi-orthogonal matrix such that UTU=Id, and f is invariant under right orthogonal transformation of U, is often referred to as a Grassmann manifold optimization. Manifold optimization appears in a wide variety of computational problems in the applied sciences. In this article, we present GrassmannOptim, an R package for Grassmann manifold optimization. The implementation uses gradient-based algorithms and embeds a stochastic gradient method for global search. We describe the algorithms, provide some illustrative examples on the relevance of manifold optimization and finally, show some practical usages of the package.

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Paper: GrassmannOptim: An R Package for Grassmann Manifold Optimization     Download PDF (Downloads: 4713)
GrassmannOptim_1.2.tar.gz: R source package Download (Downloads: 476; 7KB)
v50i05.R: R example code from the paper Download (Downloads: 555; 4KB)
marcewhole.txt: Supplementary data for example application Download (Downloads: 695; 22KB)

DOI: 10.18637/jss.v050.i05

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.