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Algebraic Descriptions of Nominal Multivariate Discrete Data

โœ Scribed by J.L. Teugels; J. Van Horebeek


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
605 KB
Volume
67
Category
Article
ISSN
0047-259X

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โœฆ Synopsis


Traditionally, multivariate discrete data are analyzed by means of log-linear models. In this paper we show how an algebraic approach leads naturally to alternative models, parametrized in terms of the moments of the distribution. Moreover we derive a complete characterization of all meaningful transformations of the components and show how transformations affect the moments of a distribution. It turns out that our models provide the necessary formal description of longitudinal data; moreover in the classical case, they can be considered as an analysis tool, complementary to log-linear models.


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