Log-mean linear models for binary data

This paper introduces a novel class of models for binary data, which we call log-mean linear models. The characterizing feature of these models is that they are specified by linear constraints on the log-mean linear parameter, defined as a log-linear expansion of the mean parameter of the multivariate Bernoulli distribution. We show that marginal independence relationships between variables can be specified by setting certain log-mean linear interactions to zero and, more specifically, that graphical models of marginal independence are log-mean linear models. Our approach overcomes some drawbacks of the existing parameterizations of graphical models of marginal independence

Gateways as inter-modal nodes in different ages: The Venetian region, eighteenth to twentieth centuries

This paper focuses on the theoretical implications of a regional case studyfor the analysis of transportation networks and gateway functions. Thestarting point is the result of a research on the changing role of gateways,and on the relocation of the gateway function from one city to a series ofcities in the Venetian region from the eighteenth to the twentieth century.Against this evolution, I test the validity and usefulness of a definition of thegateway as a point of inter-modal exchange for its historical interpretation.Changing transport technologies involve different organisations of inter-modal exchanges, and imply more or less intense economic functions ofgateway cities. These changes intertwine with political events and deci-sions, and more general economic changes: they could at the same time beread as an effect of these transformations, and as a causal factor. From this perspective, a study of intermodality shows to be useful to shed new lighton specific changes in the structure of urban hierarchie