activity
20152024
most citedFast Network Community Detection with Profile-Pseudo Likelihood Methods

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

stat.ME2024

Testing Independence Between High-Dimensional Random Vectors Using Rank-Based Max-Sum Tests

Hongfei Wang, Binghui Liu, Long Feng

In this paper, we address the problem of testing independence between two high-dimensional random vectors. Our approach involves a series of max-sum tests based on three well-known…

stat.ME2023

Fisher's combined probability test for cross-sectional independence in panel data models with serial correlation

Hongfei Wang, Binghui Liu, Long Feng +1

Testing cross-sectional independence in panel data models is of fundamental importance in econometric analysis with high-dimensional panels. Recently, econometricians began to turn…

stat.ME2022★ 1 cited

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…

stat.ME2022

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…

stat.ME2020★ 2 cited

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…

math.ST2020★ 1 cited

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…

stat.ME2015★ 1 cited

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…

stat.ME2015

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…