A scalarization technique for computing the power and exponential moments of Gaussian random matrices
type: Item
instance of: scholarly article
title: A scalarization technique for computing the power and exponential moments of Gaussian random matrices
zbMATH Open document ID: 1110.60011
DOI: 10.1155/JAMSA/2006/42542
published in: Journal of Applied Mathematics and Stochastic Analysis
publication date: 2007-03-19T00:00:00Z
full work available at URL: https://eudml.org/doc/53093
review text: Summary: We consider the problems of computing the power and exponential moments \(EX^s\) and \(Ee^{tX}\) of square Gaussian random matrices \(X=A+BWC\) for positive integer \(s\) and real \(t\), where \(W\) is a standard normal random vector and \(A\), \(B\), \(C\) are appropriately dimensioned constant matrices. We solve the problems by a matrix product scalarization technique and interpret the solutions in system-theoretic terms. The results of the paper are applicable to Bayesian prediction in multivariate autoregressive time series and mean-reverting diffusion processes.
Mathematics Subject Classification ID: 60E99
Mathematics Subject Classification ID: 15B52
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 5134591
author: Igor G. Vladimirov
author: Bevan Thompson
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 5134591