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Inference for types and structured families of commutative orthogonal block structures
Author(s) -
Francisco Carvalho,
João T. Mexia,
Carla Santos,
Célia Nunes
Publication year - 2014
Publication title -
metrika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.728
H-Index - 40
eISSN - 1435-926X
pISSN - 0026-1335
DOI - 10.1007/s00184-014-0506-8
Subject(s) - mathematics , estimator , commutative property , inference , orthogonal array , block (permutation group theory) , base (topology) , algebraic structure , variance (accounting) , class (philosophy) , statistics , discrete mathematics , pure mathematics , combinatorics , computer science , artificial intelligence , mathematical analysis , accounting , taguchi methods , business
Models with commutative orthogonal block structure, COBS, have orthogonal block structure, OBS, and their least square estimators for estimable vectors are, as it will be shown, best linear unbiased estimator, BLUE. Commutative Jordan algebras will be used to study the algebraic structure of the models and to define special types of models for which explicit expressions for the estimation of variance components are obtained. Once normality is assumed, inference using pivot variables is quite straightforward. To illustrate this class of models we will present unbalanced examples before considering families of models. When the models in a family correspond to the treatments of a base design, the family is structured. It will be shown how, under quite general conditions, the action of the factors in the base design on estimable vectors, can be studied.

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