Package: rstiefel 1.0.1

rstiefel: Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold

Simulation of random orthonormal matrices from linear and quadratic exponential family distributions on the Stiefel manifold. The most general type of distribution covered is the matrix-variate Bingham-von Mises-Fisher distribution. Most of the simulation methods are presented in Hoff(2009) "Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data" <doi:10.1198/jcgs.2009.07177>. The package also includes functions for optimization on the Stiefel manifold based on algorithms described in Wen and Yin (2013) "A feasible method for optimization with orthogonality constraints" <doi:10.1007/s10107-012-0584-1>.

Authors:Peter Hoff and Alexander Franks

rstiefel_1.0.1.tar.gz
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rstiefel_1.0.1.tgz(r-4.6-x86_64)rstiefel_1.0.1.tgz(r-4.6-arm64)rstiefel_1.0.1.tgz(r-4.5-x86_64)rstiefel_1.0.1.tgz(r-4.5-arm64)
rstiefel_1.0.1.tar.gz(r-4.7-arm64)rstiefel_1.0.1.tar.gz(r-4.7-x86_64)rstiefel_1.0.1.tar.gz(r-4.6-arm64)rstiefel_1.0.1.tar.gz(r-4.6-x86_64)
rstiefel_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rstiefel/json (API)

# Install 'rstiefel' in R:

install.packages('rstiefel', repos = c('https://pdhoff.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pdhoff/rstiefel/issues

On CRAN:

6.79 score 3 stars 11 packages 125 scripts 465 downloads 19 exports 0 dependencies

Last updated from:c19d696e35. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	114
linux-devel-x86_64	OK	105
source / vignettes	OK	176
linux-release-arm64	OK	150
linux-release-x86_64	OK	105
macos-release-arm64	OK	188
macos-release-x86_64	OK	286
macos-oldrel-arm64	OK	192
macos-oldrel-x86_64	OK	374
windows-devel	OK	70
windows-release	OK	76
windows-oldrel	OK	62
wasm-release	OK	85

Exports:lineSearch lineSearchBB NullC optStiefel rbing.matrix.gibbs rbing.O2 rbing.Op rbing.vector.gibbs rbmf.matrix.gibbs rbmf.O2 rbmf.vector.gibbs rmf.matrix rmf.matrix.gibbs rmf.vector rustiefel rW ry_bing ry_bmf tr

Dependencies:

Matrix modeling with rstiefel

Exponential families on the Stiefel manifold | Model-based SVD | Network analysis

Rendered fromrstiefel.Rnwusingutils::Sweave

Last update: 2019-02-18
Started: 2017-06-14

Help page	Topics
Random Orthonormal Matrix Generation on the Stiefel Manifold #' Simulation of random orthonormal matrices from linear and quadratic exponential family distributions on the Stiefel manifold. The most general type of distribution covered is the matrix-variate Bingham-von Mises-Fisher distribution. Most of the simulation methods are presented in Hoff(2009) "Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data" <doi:10.1198/jcgs.2009.07177>. The package also includes functions for optimzation on the Stiefel manifold based on algoirthms described in Wen and Yin (2013) "A feasible method for optimization with orthogonality constraints" <doi:10.1007/s10107-012-0584-1>.	rstiefel-package rstiefel
A curvilinear search on the Stiefel manifold (Wen and Yin 2013, Algo 1)	lineSearch
A curvilinear search on the Stiefel manifold with BB steps (Wen and Yin 2013, Algo 2) This is based on the line search algorithm described in (Zhang and Hager, 2004)	lineSearchBB
Null Space of a Matrix	NullC
Optimize a function on the Stiefel manifold	optStiefel
Gibbs Sampling for the Matrix-variate Bingham Distribution	rbing.matrix.gibbs
Simulate a 2*2 Orthogonal Random Matrix	rbing.O2
Simulate a 'p*p' Orthogonal Random Matrix	rbing.Op
Gibbs Sampling for the Vector-variate Bingham Distribution	rbing.vector.gibbs
Gibbs Sampling for the Matrix-variate Bingham-von Mises-Fisher Distribution.	rbmf.matrix.gibbs
Simulate a '2*2' Orthogonal Random Matrix	rbmf.O2
Gibbs Sampling for the Vector-variate Bingham-von Mises-Fisher Distribution	rbmf.vector.gibbs
Simulate a Random Orthonormal Matrix	rmf.matrix
Gibbs Sampling for the Matrix-variate von Mises-Fisher Distribution	rmf.matrix.gibbs
Simulate a Random Normal Vector	rmf.vector
Siumlate a Uniformly Distributed Random Orthonormal Matrix	rustiefel
Simulate 'W' as Described in Wood(1994)	rW
Helper Function for Sampling a Bingham-distributed Vector	ry_bing
Helper Function for Sampling a Bingham-von Mises-Fisher-distributed Vector	ry_bmf
Compute the trace of a matrix	tr

Package: rstiefel 1.0.1

rstiefel: Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold

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