Model Updating is frequently used in Structural Health Monitoring to determine structures'
operating conditions and whether maintenance is required. Data collected by sensors are …

This work introduces a novel methodology based on finite mixtures of Student-t distributions
to model the errors' distribution in linear regression models. The novelty lies on a particular …

This paper provides the classical and Bayesian analyses of autoregressive model having
heavy-tailed errors' distribution. We have considered a nonstandardized Student'st …

Most item response theory (IRT) models for dichotomous responses are based on probit or
logit link functions which assume a symmetric relationship between the probability of a …

On the basis of an interesting and tractable parametric family of distributions, which figures
prominently as an empirical model for asymmetric and heavy-tailed data, we introduce a …

This thesis is divided into two main parts. In the first part, we develop a new methodology
and the necessary computational tools for shape clustering. In the second part, we tackle the …