Robust methods for heteroscedastic regression models for time series

欧元对澳元的汇率波动有多大？作为心脏病的诊断工具，患者的心电图的使用能否得到改进？现有用于回答这类问题的统计方法的一个众所周知的局限性是，一小部分极端观察有可能导致结果更符合异常值，而不是与大量数据相一致。因此，统计分析可能会导致错误的结论。这个项目的目的是开发新的方法来解决这个问题，为一大类研究。在股市风险、汇率和心脏病诊断方面的应用将说明新方法。

What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bulk of the data. As a consequence, the statistical analyses may lead to wrong conclusions. This project aims to develop new methodologies to solve this problem for a large class of studies. Applications to stock market risk, exchange rate, and diagnosis of heart diseases will illustrate the new methods.