In kyoustat/RiemStiefel: Inference, Learning, and Optimization on Stiefel Manifold

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Inference, Learning, and Optimization on Stiefel Manifold

Stiefel manifold is a set of orthonormal frames in Euclidean space. We provide algorithms for statistical inference, optimization, and learning over the Stiefel manifold.

Installation

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

install.packages("RiemStiefel")

And the development version from GitHub with:

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

Available Functions

| function | description | | -------- | ----------- | | st.mean | Frechet mean computation. | | st.hclust | hierarchical agglomerative clustering. | | st.runif | random sample generation from uniform distribution. | | st.pdist | compute pairwise distance for a set of data. | | st.utestR | test of uniformity via Rayleigh-type statistic. | | stopt.SA | Simulated Annealing algorithm for optimization. |

kyoustat/RiemStiefel documentation built on March 31, 2020, 7:47 a.m.