2 citations · 2 across the 5 of their papers we have counts for
5 papers
High-dimensional outlier detection and variable selection via adaptive weighted mean regression
Jiaqi Li, Linglong Kong, Bei Jiang +1
This paper proposes an adaptive penalized weighted mean regression for outlier detection of high-dimensional data. In comparison to existing approaches based on the mean shift mode…
Simultaneous Inference of a Partially Linear Model in Time Series
Jiaqi Li, Likai Chen, Kun Ho Kim +1
We introduce a new methodology to conduct simultaneous inference of the nonparametric component in partially linear time series regression models where the nonparametric part is a…
Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM
Jiaqi Li, Likai Chen, Weining Wang +1
We propose an inference method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. Our method aggregates moving su…
Robust penalized empirical likelihood in high dimensional longitudinal data analysis
Jiaqi Li, Liya Fu
As an effective nonparametric method, empirical likelihood (EL) is appealing in combining estimating equations flexibly and adaptively for incorporating data information. To select…
Robust approach for variable selection with high dimensional Logitudinal data analysis
Liya Fu, Jiaqi Li, You-Gan Wang
This paper proposes a new robust smooth-threshold estimating equation to select important variables and automatically estimate parameters for high dimensional longitudinal data. A…