Tamas Rudas

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Conditional independence models are defined by a set of conditional independence restrictions and play an important role in many statistical applications, especially, but not only, graphical modeling. In this paper we identify a subclass of these models which are hierarchical marginal log-linear, as defined by Bergsma and Rudas (2002a). Such models are(More)
A general parametric scheme of hierarchical clustering procedures with invariance under monotone transformations of similarity values and invariance under numeration of objects is described. This scheme consists of two steps: correction of given similarity values between objects and transitive closure of obtained valued relation. Some theoretical properties(More)
First of all I wish to thank all the authors for their friendly and authoritative contributions to this special issue of the ‘Annales de la Faculté des Sciences de l’Université de Toulouse’, the editor of the ‘Annales’ for welcoming them, Stephen Fienberg and Peter van der Heijden who served as editors of this special issue. In addition to this special(More)
This dissertation proposes new applications of the Rudas-Clogg–Lindsay mixture index of fit and log-linear models that improve inferences in several areas of substantive research in political science. These include problems from electoral research–detection of electoral fraud from digit distributions, allocations of seats according to votes, territorial(More)
Variants of path models have been widely used for the analysis of the social status attainment process. The methods presented here differ from earlier approaches in several ways. Social status is considered a categorical variable and path models are developed starting from graphical models, using the marginal log-linear approach. Overall model fit may be(More)
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