Using latent variables in model based clustering: An E-government application

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.