In kyoustat/RiemGrassmann: Inference, Learning, and Optimization on Grassmann Manifold

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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

| function | description | |-------------|-----------------------------------------------------| | gr.hclust | Hierarchical clustering. | | gr.kmedoids | k-Medoids clustering. | | gr.mean | Frechet mean and variation. | | gr.pdist | Pairwise distance for Grassmann-valued data | | gr.pdist2 | Pairwise distance between two sets of data |

kyoustat/RiemGrassmann documentation built on April 1, 2020, 4:57 p.m.