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

这项研究建议关注随机变量之间的相关性。这一现象在包括健康科学、生物统计学和水文学在内的许多领域都是最令人关切的，更不用说金融和保险了。一个例子是依赖生存时间，这在临床和流行病学研究中经常遇到，例如在家庭研究、进展数据或复发事件中。Copula作为一种描述和研究随机相依性的工具正变得越来越流行，这主要是因为它在模拟变量的个体行为方面具有很大的灵活性。对这些模型的统计推断才刚刚开始出现，拟议的研究旨在促进其发展。

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.