134 citations · 135 across the 11 of their papers we have counts for
14 papers
Cauchy-Combined Hettmansperger-Randles Location Tests in High Dimensions
Ping Zhao, Long Feng, Xiaoyi Wang
High-dimensional mean testing is challenging under strong dependence and heavy tails, since classical Hotelling statistics are ill posed and regularized versions based on sample mo…
Sparse -spatial-median clustering for high-dimensional data
Ping Zhao, Dan Zhuang, Long Feng
We propose a robust clustering framework for high-dimensional data with heavy tails and a large fraction of irrelevant variables. The method replaces the mean updates of Lloyd's $K…
High dimensional alpha test for linear factor pricing model with -norm
Ping Zhao, Huifang Ma, Long Feng
We consider testing zero pricing errors in high-dimensional linear factor pricing models. Existing methods are mainly based on either an statistic, which is effective under d…
Note on High Dimensional Spatial-Sign Test for One Sample Problem
Ping Zhao, Long Feng
We revisit the null distribution of the high-dimensional spatial-sign test of Wang et al. (2015) under mild structural assumptions on the scatter matrix. We show that the standardi…
Inverse Norm Weighted Maxsum Test for High Dimensional Location Parameters
Guowei Yan, Ping Zhao, Long Feng
In the context of high-dimensional data, we investigate the one-sample location testing problem. We introduce a max-type test based on the weighted spatial sign, which exhibits exc…
Robust Mutual Fund Selection with False Discovery Rate Control
Hongfei Wang, Long Feng, Ping Zhao +1
In this article, we address the challenge of identifying skilled mutual funds among a large pool of candidates, utilizing the linear factor pricing model. Assuming observable facto…
Adaptive Sphericity Tests for High Dimensional Data
Ping Zhao, Wenwan Yang, Long Feng +1
In this paper, we investigate sphericity testing in high-dimensional settings, where existing methods primarily rely on sum-type test procedures that often underperform under spars…
Adaptive L-statistics for high dimensional test problem
Huifang Ma, Long Feng, Zhaojun Wang
In this study, we focus on applying L-statistics to the high-dimensional one-sample location test problem. Intuitively, an L-statistic with parameters tends to perform optimall…
Double Robust high dimensional alpha test for linear factor pricing model
Ping Zhao, Long Feng, Hongfei Wang +1
In this paper, we investigate alpha testing for high-dimensional linear factor pricing models. We propose a spatial sign-based max-type test to handle sparse alternative cases. Add…
Spatial Sign based Principal Component Analysis for High Dimensional Data
Ping Zhao, Hongfei Wang, Long Feng
This article focuses on the robust principal component analysis (PCA) of high-dimensional data with elliptical distributions. We investigate the PCA of the sample spatial-sign cova…
Adaptive Strategy of Testing Alphas in High Dimensional Linear Factor Pricing Models
Chenxi Zhao, Ping Zhao, Long Feng +1
In recent years, there has been considerable research on testing alphas in high-dimensional linear factor pricing models. In our study, we introduce a novel max-type test procedure…
Spatial-Sign based Maxsum Test for High Dimensional Location Parameters
Jixuan Liu, Long Feng, Ping Zhao +1
In this study, we explore a robust testing procedure for the high-dimensional location parameters testing problem. Initially, we introduce a spatial-sign based max-type test statis…
Testing Alpha in High Dimensional Linear Factor Pricing Models with Dependent Observations
Huifang Ma, Long Feng, Zhaojun Wang +1
In this study, we introduce three distinct testing methods for testing alpha in high dimensional linear factor pricing model that deals with dependent data. The first method is a s…
Nonparametric maximum likelihood approach to multiple change-point problems
Changliang Zou, Guosheng Yin, Long Feng +1
In multiple change-point problems, different data segments often follow different distributions, for which the changes may occur in the mean, scale or the entire distribution from…