New nonparametric statistical methods for imperfectly observed data

今天的统计科学正面临着必须回答比以往任何时候都更加复杂的数据问题的挑战。一些主要的困难是由于不能直接获得感兴趣的数据量，以及现有数据的结构比较复杂。在癌症和遗传研究、传染病、环境污染、公共卫生和营养等领域的应用的推动下，该项目旨在开发新颖而高效的统计方法，以解决涉及新型不完全观测数据的当代问题。预期的结果将解决前沿问题，在这些问题中，信息只能通过复杂的计算机密集型方法获得。

Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutrition, this project aims to develop novel and highly effective statistical methodology for solving contemporary problems involving new types of imperfectly observed data. The expected outcomes will solve frontier problems, where information can only be accessed through sophisticated computer intensive methods.