1 citations · 3 across the 5 of their papers we have counts for
6 papers
Testing for high-dimensional white noise
Long Feng, Binghui Liu, Yanyuan Ma
Testing for multi-dimensional white noise is an important subject in statistical inference. Such test in the high-dimensional case becomes an open problem waiting to be solved, esp…
Asymptotic Independence of the Sum and Maximum of Dependent Random Variables with Applications to High-Dimensional Tests
Long Feng, Tiefeng Jiang, Xiaoyun Li +1
For a set of dependent random variables, without stationary or the strong mixing assumptions, we derive the asymptotic independence between their sums and maxima. Then we apply thi…
Fast Network Community Detection with Profile-Pseudo Likelihood Methods
Jiangzhou Wang, Jingfei Zhang, Binghui Liu +2
The stochastic block model is one of the most studied network models for community detection. It is well-known that most algorithms proposed for fitting the stochastic block model…
Max-sum tests for cross-sectional dependence of high-demensional panel data
Long Feng, Tiefeng Jiang, Binghui Liu +1
We consider a testing problem for cross-sectional dependence for high-dimensional panel data, where the number of cross-sectional units is potentially much larger than the number o…
High Dimensional Spatial Rank Test for Two-Sample Location Problem
Long Feng
This article concerns tests for the two-sample location problem when the dimension is larger than the sample size. The traditional multivariate-rank-based procedures cannot be used…
High Dimensional Rank Tests for Sphericity
Long Feng
Sphericity test plays a key role in many statistical problems. We propose Spearman's rho-type rank test and Kendall's tau-type rank test for sphericity in the high dimensional sett…