most citedScalar-Invariant Test for High-Dimensional Regression Coefficients

1 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

stat.ME20221 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…

cs.CV20221 cited

Sparse Kronecker Product Decomposition: A General Framework of Signal Region Detection in Image Regression

Sanyou Wu, Long Feng

This paper aims to present the first Frequentist framework on signal region detection in high-resolution and high-order image regression problems. Image data and scalar-on-image re…

stat.ME2015

Optimal Sign Test for High Dimensional Location Parameters

Long Feng

This article concerns tests for location parameters in cases where the data dimension is larger than the sample size. We propose a family of tests based on the optimality arguments…

stat.ME20151 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

Spatial-Sign based High-Dimensional Location Test

Long Feng, Fasheng Sun

In this paper, we consider the problem of testing the mean vector in the high dimensional settings. We proposed a new robust scalar transform invariant test based on spatial sign.…

stat.ME2015

A Note on High Dimensional Two Sample Mean Test

Long Feng, Fasheng Sun

In this paper, we propose a new scalar and shift transform invariant test statistic for the high-dimensional two-sample location test. The expectation of our test is exactly zero u…