3 papers
stat.ME2026
Shape-Preserving Covariate Adjustment via Empirical Likelihood in Randomized Experiment
Zhilan Lou, Jun Shao, Yuhan Qian +4
Covariate adjustment improves estimation efficiency in randomized experiments, but standard calibration and augmentation methods, when applied to distribution or survival functions…
stat.ME2026
Covariate Adjustment for Wilcoxon Two Sample Statistic and Test
Zhilan Lou, Jun Shao, Ting Ye +3
We apply covariate adjustment to the Wincoxon two sample statistic and Wincoxon-Mann-Whitney test in comparing two treatments. The covariate adjustment through calibration not only…
stat.OT2022
An empirical exploration of the diversified R ecosystem
Tian-Yuan Huang, Zhilan Lou
Born in the late 20s, R is one of the most popular software for statistical computing and graphics. With the development of information technology and the advent of the big data er…