package-RiemGrassmann

<p>Grassmann manifold $Gr(k,n)$ is the set of k-planes, or $k$-dimensional subspaces in $R^n$, 
which is indeed a compact Riemannian manifold. In this package, we use a convention that each element 
in $Gr(k,n)$ is represented as an orthonormal basis (ONB) $X \in \mathbf{R}^{n\times k}$ where
$$X^\top X = I_k$$.</p>

Grassmann manifold is a set of k-planes or linear subspaces in Euclidean space. We provide algorithms for statistical inference, optimization, and learning over the Grassmann manifold. For general exposition to the statistics on the manifold, see the book by Chikuse (2003) <doi:10.1007/978-0-387-21540-2>.

package-RiemGrassmann: Inference, Learning, and Optimization on Grassmann Manifold

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