Mathematical Sciences: Statistical Models and Methods for Incomplete and Biased Data

本研究的重点是发展模型和方法的统计分析有偏差，或不完整的数据。问题将在三个不同的一般研究领域解决：(1)更新过程中的估计；(2)选择偏差中的半参数模型；(3)横截面抽样的统计模型。统计学的这项工作旨在改进处理数据采集中的抽样偏差和不完整性的可用工具。近年来艾滋病的蔓延，以及在抽样、诊断和识别患者过程中涉及的行为问题，迫切需要为各种复杂的有偏差抽样方案开发这样的方法。在发展统计模型和方法时，这些问题将得到解决。

This research focuses on the development of models and methods for statistical analysis of biased, or incomplete, data. Problems will be tackled in three different general research areas: (1) Estimation in Renewal Processes, (2) Semiparametric Models in Selection Bias, and (3) Statistical Models for Cross Sectional Sampling. This work in statistics aims at improving the tools available for handling sampling bias and incompleteness in data acquisition. The recent spread of the AIDS epidemic, and the behavioral issues involved in sampling, diagnosing, and identifying patients present a pressing need for the development of such methods for a variety of complicated biased-sampling schemes. In developing the statistical models and methods, these issues will be addressed.