Inference in Error Orthogonal Models

Francisco Carvalho () and João Tiago Mexia
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Francisco Carvalho: Instituto Politécnico de Tomar, Unidade Departamental de Matemática e Física
João Tiago Mexia: Universidade Nova de Lisboa, CMA—Centro de Matemática e Aplicações

A chapter in Combinatorial Matrix Theory and Generalized Inverses of Matrices, 2013, pp 85-100 from Springer

Abstract: Abstract Error Orthogonal Models constitute a very interesting class of models very useful in the design of experiments. The use of commutative Jordan algebras of symmetric matrices is used in order to perform statistical inference. The concept of segregation is introduced thus allowing the estimation of variance components.

Keywords: Error Orthogonal; Jordan algebras; Segregation; Variance components; 62K99; 62J10; 62H12 (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-81-322-1053-5_8

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DOI: 10.1007/978-81-322-1053-5_8

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