Supporting Information Mustonen et alpnasSI Text Abf1 and Reb1 Energy Matrices and Site Ensembles. The energy matrices used in this study, as well as the Q4 site ensembles, are available for downloa

Source URL: www.thp.uni-koeln.de

The Sparse Matrices Package. Sparse Matrix Calculations and a Linear Algebra Package for Sparse Matrices in REDUCE Stephen Scowcroft Konrad-Zuse-Zentrum f¨ ur Informationstechnik Berlin

Source URL: www.reduce-algebra.com

Symmetric Rigid Body Equations, Flows on Symmetric Matrices, and Optimal Control Anthony M. Bloch∗ Department of Mathematics University of Michigan Ann Arbor MI 48109

Source URL: www.uantwerpen.be

INVITED PAPER Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments

Source URL: www.stat.berkeley.edu

• Numerical linear algebra
• Matrices
• Matrix theory
• Linear algebra
• Econometrics
• Linear regression
• Preconditioner
• Algorithm
• Singular value decomposition
• Linear programming
• Condition number
• Regression analysis

Stress Matrices and M Matrices Robert Connelly (joint work with K´aroly Bezdek) 1. Introduction In [2] a connection is made between what are called “M” matrices, as used

Source URL: www.math.cornell.edu

Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices Ayan Acharya Dept. of ECE, UT Austin

Source URL: jmlr.org

University of California, Irvine Statistics Seminar A Tractable State-space Model for Dynamic Covariance Matrices

Source URL: www.stat.uci.edu

1 MARCHSCHNEIDER 853

Source URL: climate-dynamics.org

• Statistics
• Regression analysis
• Estimation theory
• Multivariate statistics
• Covariance and correlation
• Matrices
• Covariance
• Linear regression
• Tikhonov regularization
• Sample mean and covariance
• Principal component analysis
• Principal component regression

Comm. AlgebraINTEGRALLY CLOSED DOMAINS, MINIMAL POLYNOMIALS, AND NULL IDEALS OF MATRICES SOPHIE FRISCH Abstract. We show that every element of the integral closure D0 of a domain

Source URL: blah.math.tu-graz.ac.at

Parameter inference with estimated covariance matrices Elena Sellentin Institut für Theoretische Physik Universität Heidelberg arXiv: 1511:05969

Source URL: cosmo21.cosmostat.org