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Inference in Error Orthogonal Models

In: Combinatorial Matrix Theory and Generalized Inverses of Matrices

Author

Listed:
  • Francisco Carvalho

    (Instituto Politécnico de Tomar, Unidade Departamental de Matemática e Física
    Universidade Nova de Lisboa, CMA—Centro de Matemática e Aplicações)

  • João Tiago Mexia

    (Universidade Nova de Lisboa, CMA—Centro de Matemática e Aplicações
    Universidade Nova de Lisboa, Departamento de Matemática, Faculdade Ciências e Tecnologia)

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.

Suggested Citation

  • Francisco Carvalho & João Tiago Mexia, 2013. "Inference in Error Orthogonal Models," Springer Books, in: Ravindra B. Bapat & Steve J. Kirkland & K. Manjunatha Prasad & Simo Puntanen (ed.), Combinatorial Matrix Theory and Generalized Inverses of Matrices, edition 127, pages 85-100, Springer.
    • Handle: RePEc:spr:sprchp:978-81-322-1053-5_8
    DOI: 10.1007/978-81-322-1053-5_8
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