In this paper we outline an alternative derivation of the square-root-free Cholesky decomposition of P - pp' based on square-root-free variants of a standard algorithm in statistical computing.
Similar issue has been report also in #2015. While I love the new cholesky decomposed covariance matrix in MvNormal, setting it as a default is numerical quite ...
Abstract: The Cholesky decomposition represents a fundamental building block in order to solve several matrix-related problems, ranging from matrix inversion to determinant calculation, and it finds ...
We propose new regression models for parameterizing covariance structures in longitudinal data analysis. Using a novel Cholesky factor, the entries in this decomposition have a moving average and ...
Department of Theoretical Chemistry, Chemical Center, University of Lund, P.O. Box 124 S-221 00 Lund, Sweden, and Department of Physical Chemistry, Sciences II, University of Geneva, Quai E. Ansermet ...
To reconstruct a SymDense from the cholesky decomposition, we currently use SymOuterK. There is apparently an explicitly lapack function for computing L^T * L (Dlauum). We should use that instead.
A version of this document that discusses the complex valued case can be found here . This material is probably best suited to students who have had a course in linear algebra already. Given a SPD ...
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