2 citations · 3 across the 11 of their papers we have counts for
11 papers
Efficient Poisson Subsampling for the Partially Linear Additive Cox Model
Dongxiao Han, Liuquan Sun, Chunjie Wang +3
To address the computational and storage challenges often encountered in large-scale survival data analysis, we propose an efficient Poisson subsampling method for the partially li…
Causal inference for censored data with continuous marks
Lianqiang Qu, Long Lv, Liuquan Sun
This paper presents a framework for causal inference in the presence of censored data,where the failure time is marked by a continuous variable referred to as a mark.The mark is ob…
Gaussian Multiplier Bootstrap Procedure for the th Largest Coordinate of High-Dimensional Statistics
Yixi Ding, Qizhai Li, Yuke Shi +2
We consider the problem of Gaussian multiplier bootstrap procedures for the th largest statistics and functions of the top order statistics, which are commonly encountered i…
Conditional inference for high-dimensional multi-omics survival data
Heyuan Zhang, Meiling Hao, Lianqiang Qu +1
Multi-omics data present significant challenges for statistical inference due to the complex interdependencies among biological layers. In this paper, we introduce a novel Multi-Om…
Linear spline index regression model: Interpretability, nonlinearity and dimension reduction
Lianqiang Qu, Long Lv, Meiling Hao +1
Inspired by the complexity of certain real-world datasets, this article introduces a novel flexible linear spline index regression model. The model posits piecewise linear effects…
Distributed variable screening for generalized linear models
Tianbo Diao, Lianqiang Qu, Bo Li +1
In this article, we develop a distributed variable screening method for generalized linear models. This method is designed to handle situations where both the sample size and the n…
A new First-Order mixture integer-valued threshold autoregressive process based on binomial thinning and negative binomial thinning
Danshu Sheng, Dehui Wang, Liuquan Sun
In this paper, we introduce a new first-order mixture integer-valued threshold autoregressive process, based on the binomial and negative binomial thinning operators. Basic probabi…
Renewable Learning for Multiplicative Regression with Streaming Datasets
Tianzhen Wang, Haixiang Zhang, Liuquan Sun
When large amounts of data continuously arrive in streams, online updating is an effective way to reduce storage and computational burden. The key idea of online updating is that t…
Inference on High-dimensional Single-index Models with Streaming Data
Dongxiao Han, Jinhan Xie, Jin Liu +4
Traditional statistical methods are faced with new challenges due to streaming data. The major challenge is the rapidly growing volume and velocity of data, which makes storing suc…
Approximating Partial Likelihood Estimators via Optimal Subsampling
Haixiang Zhang, Lulu Zuo, HaiYing Wang +1
With the growing availability of large-scale biomedical data, it is often time-consuming or infeasible to directly perform traditional statistical analysis with relatively limited…
On Estimating Optimal Regime for Treatment Initiation Time Based on Restricted Mean Residual Lifetime
Xin Chen, Rui Song, Jiajia Zhang +3
When to initiate treatment on patients is an important problem in many medical studies such as AIDS and cancer. In this article, we formulate the treatment initiation time problem…