Learn R Programming

Inference, Learning, and Optimization on Grassmann manifold

Grassmannian is a set of linear subspaces, which forms a Riemannian manifold. We provide algorithms for statistical inference, optimization, and learning over the Grassmann manifold.

Installation

You can install the released version of RiemGrassmann from CRAN with:

install.packages("RiemGrassmann")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("kyoustat/RiemGrassmann")

Available Functions

functiondescription
gr.hclustHierarchical clustering.
gr.kmedoidsk-Medoids clustering.
gr.meanFrechet mean and variation.
gr.pdistPairwise distance for Grassmann-valued data
gr.pdist2Pairwise distance between two sets of data

Copy Link

Version

Install

install.packages('RiemGrassmann')

Monthly Downloads

6

Version

0.1.0

License

GPL (>= 3)

Maintainer

Kisung You

Last Published

March 25th, 2020

Functions in RiemGrassmann (0.1.0)

package-RiemGrassmann

Inference, Learning, and Optimization on Grassmann Manifold
gr.pdist2

Pairwise Distance for Two Sets Data on Grassmann Manifold
gr.kmedoids

k-Medoids Clustering on Grassmann Manifold
gr.pdist

Pairwise Distance for Data on Grassmann Manifold
gr.mean

Fr<U+00E9>chet Mean on Grassmann Manifold
gr.hclust

Hierarchical Agglomerative Clustering on Grassmann Manifold