报告题目：Melded Confidence Intervals Do Not Provide Guaranteed Coverage
报 告 人：张一旻 副教授 （Villanova University）
报告时间：2024年6月20日 （星期四）上午10：00-11：00
报告地点：数学楼114（小报告厅）
邀 请 人：王晓光 副教授 联系电话：84708354
报告摘要：Melded confidence intervals were proposed as a way to combine two independent one-sample confidence intervals to obtain a two-sample confidence interval for a quantity like a difference or a ratio. Simulation-based work has suggested that melded confidence intervals always provide at least the nominal coverage. However, we show here that for the case of melded confidence intervals for a difference in population quantiles, the confidence intervals do not guarantee the nominal coverage. We derive a lower bound on the coverage for a one-sided confidence interval, and we show that there are pairs of distributions that make the coverage arbitrarily close to this lower bound. One specific example of our results is that the 95% melded upper bound on the difference between two population medians offers a guaranteed coverage of only 88.3% when both samples are of size 20.
报告人简介：Dr. Yimin Zhang is an associate professor of statistics in Department of Mathematics and Statistics at Villanova University. Her research interests include nonparametric statistics, inference on ranked set sampling, statistical modeling and machine learning. Her recent collaborative work spans environmental science, sustainability and transportation.
