3 papers
stat.AP2025
On the super-efficiency and robustness of the least squares of depth-trimmed regression estimator
Yijun Zuo, Hanwen Zuo
The least squares of depth-trimmed (LST) residuals regression, proposed and studied in Zuo and Zuo (2023), serves as a robust alternative to the classic least squares (LS) regressi…
stat.ME2023
Weighted least squares regression with the best robustness and high computability
Yijun Zuo, Hanwen Zuo
A novel regression method is introduced and studied. The procedure weights squared residuals based on their magnitude. Unlike the classic least squares which treats every squared r…
stat.ME2023
Computation of least squares trimmed regression--an alternative to least trimmed squares regression
Yijun Zuo, Hanwen Zuo
The least squares of depth trimmed (LST) residuals regression, proposed in Zuo and Zuo (2023) \cite{ZZ23}, serves as a robust alternative to the classic least squares (LS) regressi…