4 papers
Limiting spectral distributions of large consistent rank correlation matrices
Zhaorui Dong, Fang Han, Jianfeng Yao
We study random matrices whose entries are obtained by applying consistent rank correlations, such as Hoeffding's , pairwise to a high-dimensional random vector with mutually in…
Many-sample tests for the dimensionality hypothesis for large covariance matrices among groups
Tianxing Mei, Chen Wang, Jianfeng Yao
In this paper, we consider procedures for testing hypotheses on the dimension of the linear span generated by a growing number of covariance matrices from independent $…
Many-sample tests for the equality and the proportionality hypotheses between large covariance matrices
Tianxing Mei, Chen Wang, Jianfeng Yao
This paper proposes procedures for testing the equality hypothesis and the proportionality hypothesis involving a large number of covariance matrices of dimension .…
Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix
Jiaxin Qiu, Zeng Li, Jianfeng Yao
Determining the number of factors in high-dimensional factor modeling is essential but challenging, especially when the data are heavy-tailed. In this paper, we introduce a new est…