Analysis of Absolute Deviation, Inference and Model Selection

点击翻译按钮获取中文摘要

This project develops a comprehensive approach to estimation,model selection and inferences for certain regression models, withapplications to health sciences, economics, astronomy as well asother disciplines of scientific investigations. Various parts ofthe project are connected through several key components:computational aspect is handled by linear programming, inferencesby simulation-based resampling, simultaneous estimation and modelselection by suitably constructed penalty functions, andasymptotic properties by empirical process theory. Theinvestigator develops efficient algorithms for parameterestimation and distributional approximation, establishes small andlarge sample properties, and extends the methods and theory todata with censoring, truncation or other kind of non-randommissingness.This research project is motivated by and closely related to manyimportant areas of scientific disciplines, including health andlife sciences, economics, astronomy and sociology. It develops newtools to assess health risks, drugs and treatments effects andgenetic variations, to analyze policy formation, such asintervention in unemployment and health insurance, as well as tounderstand astronomical phenomena. It provides a platform toattract and train students with tools for multi-disciplinaryapplications.