Algebraic Descriptions of Nominal Multivariate Discrete Data

J. L. Teugels and J. Van Horebeek

Journal of Multivariate Analysis, 1998, vol. 67, issue 2, 203-226

Abstract: 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.

Keywords: multivariate; discrete; distributions; categorical; data; log-linear; models; marginal; homogeneity (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (3)

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