2 papers
stat.ME2025
Semi-supervised learning for linear extremile regression
Rong Jiang, Keming Yu, Jiangfeng Wang
Extremile regression, as a least squares analog of quantile regression, is potentially useful tool for modeling and understanding the extreme tails of a distribution. However, exis…
math.ST2025
Average quantile regression: a new non-mean regression model and coherent risk measure
Rong Jiang, M. C. Jones, Keming Yu +1
Regression models that go beyond the mean, alongside coherent risk measures, have been important tools in modern data analysis. This paper introduces the innovative concept of Aver…