Maximum Likelihood Estimation in the Tensor Normal Model with a Structured Mean
2015 (English)Report (Other academic)
There is a growing interest in the analysis of multi-way data. In some studies the inference about the dependencies in three-way data is done using the third order tensor normal model, where the focus is on the estimation of the variance-covariance matrix which has a Kronecker product structure. Little attention is paid to the structure of the mean, though, there is a potential to improve the analysis by assuming a structured mean. In this paper, we introduce a 2-fold growth curve model by assuming a trilinear structure for the mean in the tensor normal model and propose an algorithm for estimating parameters. Also, some direct generalizations are presented.
Place, publisher, year, edition, pages
Linköping University Electronic Press, 2015. , 16 p.
LiTH-MAT-R, ISSN 0348-2960 ; 2015-:08
growth curve model, Kronecker product structure, maximum likelihood estimators, multi-way data, tensor normal model, trilinear regression
IdentifiersURN: urn:nbn:se:liu:diva-117512ISRN: LiTH-MAT-R--2015/08--SEOAI: oai:DiVA.org:liu-117512DiVA: diva2:808970