Nov 22, 2022 · This paper revisits the celebrated Hodges-Lehmann (HL) estimator for estimating location parameters in both the one- and two-sample problems, from a non- ...

Our study develops Berry–Esseen inequality and Cramér-type moderate deviation for the HL estimator based on newly developed nonasymptotic Bahadur representation ...

These results allow us to extend the HL estimator to large-scale studies and propose tuning-free and moment-free high-dimensional inference procedures for ...

Nov 23, 2022 · These results allow us to extend the HL estimator to large-scale studies and propose tuning-free and moment-free high-dimensional inference ...

Oct 22, 2024 · This paper presents a design technique for the synthesis of robust observers for linear dynamical systems with uncertain parameters. The ...

Oct 22, 2024 · It is robust with substantial efficiency gain for heavy-tailed random errors while maintaining high efficiency for normal random errors.

Dec 18, 2020 · It uses an easily simulated tuning parameter that automatically adapts to both the unknown random error distribution and the correlation ...

This paper gives a selective overview on recent advance on high-dimensional factor models and their applications to statistics.

A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation · A Survey of Tuning Parameter Selection for High-dimensional Regression.

In this paper, we propose explicit algorithms to solve multiple sparse estimation problems with high performances in all previous aspects. In particular, our ...