Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
type: Item
instance of: scholarly article
title: Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
zbMATH Open document ID: 1255.65029
author: Ameur M. Manceur
author: Pierre Dutilleul
published in: Journal of Computational and Applied Mathematics
publication date: 2013-01-14T00:00:00Z
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 6125288
zbMATH Keywords: empirical bias and dispersion
zbMATH Keywords: maximum likelihood estimation
zbMATH Keywords: minimum sample size
zbMATH Keywords: multi-stage algorithm
zbMATH Keywords: separable variance-covariance structure
zbMATH Keywords: tensor normal distribution
describes a project that uses: Ziggurat
describes a project that uses: Matlab
MaRDI profile type: Publication
full work available at URL: j.cam.2012.09.017
OpenAlex ID: W2030434042
Wikidata QID: Q123344808
DOI: 10.1016/J.CAM.2012.09.017
description: scientific article; zbMATH DE number 6125288