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

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rstiefel.pdf |rstiefel.html✨
rstiefel/json (API)
NEWS

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

Peer review:

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

On CRAN:

6.43 score 3 stars 7 packages 86 scripts 309 downloads 19 exports 0 dependencies

Last updated 3 years agofrom:c19d696e35. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64OKOct 31 2024
R-4.5-linux-x86_64OKOct 31 2024
R-4.4-win-x86_64OKOct 31 2024
R-4.4-mac-x86_64OKOct 31 2024
R-4.4-mac-aarch64OKOct 31 2024
R-4.3-win-x86_64OKOct 31 2024
R-4.3-mac-x86_64OKOct 31 2024
R-4.3-mac-aarch64OKOct 31 2024

Exports:lineSearchlineSearchBBNullCoptStiefelrbing.matrix.gibbsrbing.O2rbing.Oprbing.vector.gibbsrbmf.matrix.gibbsrbmf.O2rbmf.vector.gibbsrmf.matrixrmf.matrix.gibbsrmf.vectorrustiefelrWry_bingry_bmftr

Dependencies:

Matrix modeling with rstiefel

Rendered fromrstiefel.Rnwusingutils::Sweaveon Oct 31 2024.

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

Readme and manuals

Help Manual

Help pageTopics
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 MatrixNullC
Optimize a function on the Stiefel manifoldoptStiefel
Gibbs Sampling for the Matrix-variate Bingham Distributionrbing.matrix.gibbs
Simulate a 2*2 Orthogonal Random Matrixrbing.O2
Simulate a 'p*p' Orthogonal Random Matrixrbing.Op
Gibbs Sampling for the Vector-variate Bingham Distributionrbing.vector.gibbs
Gibbs Sampling for the Matrix-variate Bingham-von Mises-Fisher Distribution.rbmf.matrix.gibbs
Simulate a '2*2' Orthogonal Random Matrixrbmf.O2
Gibbs Sampling for the Vector-variate Bingham-von Mises-Fisher Distributionrbmf.vector.gibbs
Simulate a Random Orthonormal Matrixrmf.matrix
Gibbs Sampling for the Matrix-variate von Mises-Fisher Distributionrmf.matrix.gibbs
Simulate a Random Normal Vectorrmf.vector
Siumlate a Uniformly Distributed Random Orthonormal Matrixrustiefel
Simulate 'W' as Described in Wood(1994)rW
Helper Function for Sampling a Bingham-distributed Vectorry_bing
Helper Function for Sampling a Bingham-von Mises-Fisher-distributed Vectorry_bmf
Compute the trace of a matrixtr