1 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…