Identifiability of Discrete Hierarchical Models with One Latent Variable

In the thesis we discuss in depth the problem of identifiability for discrete models, showing many concrete situations in which it may fail. After this survey we concentrate on hierarchical log-linear models for binary variables with one hidden variable. These are more general of the LC models because may include some higher-order interactions. These models may sometimes be interpreted as discrete undirected graphical models (called also concentration graph models), but they are more general.