8 citations · 8 across the 5 of their papers we have counts for
5 papers
Feature screening for multi-response linear models by empirical likelihood
Jun Lu, Qinqin Hu, Lu Lin
This paper proposes a new feature screening method for the multi-response ultrahigh dimensional linear model by empirical likelihood. Through a multivariate moment condition, the e…
Online Updating Statistics for Heterogenous Updating Regressions via Homogenization Techniques
Lin Lu, Lu Jun, Li Weiyu
Under the environment of big data streams, it is a common situation where the variable set of a model may change according to the condition of data streams. In this paper, we propo…
Unified Rules of Renewable Weighted Sums for Various Online Updating Estimations
Lu Lin, Weiyu Li, Jun Lu
This paper establishes unified frameworks of renewable weighted sums (RWS) for various online updating estimations in the models with streaming data sets. The newly defined RWS lay…
A race-DC in Big Data
Lu Lin, Jun Lu
The strategy of divide-and-combine (DC) has been widely used in the area of big data. Bias-correction is crucial in the DC procedure for validly aggregating the locally biased esti…
Group-Average and Convex Clustering for Partially Heterogeneous Linear Regression
Lu Lin, Jun Lu, Chen Lin
In this paper, a subgroup least squares and a convex clustering are introduced for inferring a partially heterogenous linear regression that has potential application in the areas…