Segregation and intrinsec restrictions on canonic variance components

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Abstract

This paper deals with the estimability of variance components, in mixed models, when the dimension of the commutative algebra, spanned by all possible variance-covariance matrices, is greater than the number of linearly independent unknown variance components. As example we present an application to a random three-factor crossed-model.
Original languageEnglish
Title of host publicationInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
EditorsCharalambos Tsitouras, Theodore Simos
PublisherAmerican Institute of Physics (AIP)
Number of pages5
ISBN (Electronic)978-073541690-1
DOIs
Publication statusPublished - 10 Jul 2018
EventInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017 - Thessaloniki, Greece
Duration: 25 Sept 201730 Sept 2017

Publication series

NameAIP Conference Proceedings
PublisherAmerican Institute of Physics (AIP)
Volume1978
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
Country/TerritoryGreece
CityThessaloniki
Period25/09/1730/09/17

Keywords

  • Inference
  • linear models
  • variance components

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