Inference for copula-based dependence models with discrete or incomplete data

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This research proposal is concerned with dependence between random variables. This phenomenon is of prime concern in many fields, including health sciences, biostatistics and hydrology, not to speak of finance and insurance. An example is provided by dependent survival times, which are often encountered in clinical and epidemiological research, e.g., in family studies, progression data or recurrent events. Copulas are becoming increasingly popular as a tool for the characterization and study of stochastic dependence, mainly due to their great flexibility in modeling the variables' individual behavior. Statistical inference for these models is only beginning to emerge and the proposed research aims at contributing towards its development.