Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold


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Documentation for package ‘rstiefel’ version 1.0.1

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rstiefel-package 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>.
lineSearch A curvilinear search on the Stiefel manifold (Wen and Yin 2013, Algo 1)
lineSearchBB 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)
NullC Null Space of a Matrix
optStiefel Optimize a function on the Stiefel manifold
rbing.matrix.gibbs Gibbs Sampling for the Matrix-variate Bingham Distribution
rbing.O2 Simulate a 2*2 Orthogonal Random Matrix
rbing.Op Simulate a 'p*p' Orthogonal Random Matrix
rbing.vector.gibbs Gibbs Sampling for the Vector-variate Bingham Distribution
rbmf.matrix.gibbs Gibbs Sampling for the Matrix-variate Bingham-von Mises-Fisher Distribution.
rbmf.O2 Simulate a '2*2' Orthogonal Random Matrix
rbmf.vector.gibbs Gibbs Sampling for the Vector-variate Bingham-von Mises-Fisher Distribution
rmf.matrix Simulate a Random Orthonormal Matrix
rmf.matrix.gibbs Gibbs Sampling for the Matrix-variate von Mises-Fisher Distribution
rmf.vector Simulate a Random Normal Vector
rstiefel 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>.
rustiefel Siumlate a Uniformly Distributed Random Orthonormal Matrix
rW Simulate 'W' as Described in Wood(1994)
ry_bing Helper Function for Sampling a Bingham-distributed Vector
ry_bmf Helper Function for Sampling a Bingham-von Mises-Fisher-distributed Vector
tr Compute the trace of a matrix