Title: Model based clustering for young stars clusters
Abstract: Model based clustering is a method of fitting finite mixtures models to data in order to identify clusters. It is widely used in many fields and has a variety of applications, one of those is the identification of young star clusters. We will examine four different models multivariate Gaussian, t, Skew Normal and Skew t mixtures and a method that suggests combining normal components to form a cluster. we will analyze their characteristics and we will then apply them to a real dataset of young stars in order to evaluate their performance in this specific problem.