Abstract
Besides continuous variables, binary indicators on ICT (Information and Communication Technologies) infrastructures and utilities are usually collected in order to evaluate the quality of a public company and to define the policy priorities. In this chapter, we confront the problem of clustering public organizations with model-based clustering, and we assume each observed binary indicator to be generated from a latent continuous variable. The estimates of the scores of these variables allow us to use a fully Gaussian mixture model for classification.
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Morlini, I. (2013). Using Latent Variables in Model Based Clustering: An E-Government Application. In: Oliveira, P., da Graça Temido, M., Henriques, C., Vichi, M. (eds) Recent Developments in Modeling and Applications in Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32419-2_1
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DOI: https://doi.org/10.1007/978-3-642-32419-2_1
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