Modeling Dependent and Incomplete Data: A Study of Certain Estimators

Résumé

The aim of this thesis is to propose models based on incomplete and dependent data. Incomplete data, in particular censoring and/or truncation, have been widely studied for decades, using both parametric and non-parametric methods. These studies have most often the independent nature of the data. On the other hand, dependent data have come to be used in practical life, and several types of dependence are based on real-life cases. In this work, we will focus on a WOD (Widely Orthant Dependence). We will then study the asymptotic behavior of certain non-parametric estimators of statistical functionals.

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