TY - JOUR
T1 - Estimating the number of equal components for two high-dimensional mean vectors
AU - Yu, Wei
AU - Xu, Wangli
AU - Zhu, Lixing
N1 - Funding Information:
The research described herewith was supported by a grant from The University Grants Council of Hong Kong; an NSFC grant (NSFC11671042); and a grant by Natural Science Foundation of Anhui Province (1908085QA07).
Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
PY - 2021/8/31
Y1 - 2021/8/31
N2 - In this article, we propose a new method for estimating the number of equal components m 0 of two m-dimensional population means when m is large. The proposed method can be used to estimate the number of equally expressed or differentially expressed genes in DNA microarray studies. It can also be applied in the step of estimating m 0 in adaptive false discovery rate controlling procedures. Simulation results show that the bias of the moment estimator is very small for both normal and non normal data. It has higher precision than existing methods in most cases. It has more evident advantage under non normal data.
AB - In this article, we propose a new method for estimating the number of equal components m 0 of two m-dimensional population means when m is large. The proposed method can be used to estimate the number of equally expressed or differentially expressed genes in DNA microarray studies. It can also be applied in the step of estimating m 0 in adaptive false discovery rate controlling procedures. Simulation results show that the bias of the moment estimator is very small for both normal and non normal data. It has higher precision than existing methods in most cases. It has more evident advantage under non normal data.
KW - DNA microarray analysis
KW - false discovery rate
KW - high-dimensional data
KW - Multiple hypothesis testing
UR - http://www.scopus.com/inward/record.url?scp=85079393691&partnerID=8YFLogxK
U2 - 10.1080/03610926.2020.1722842
DO - 10.1080/03610926.2020.1722842
M3 - Journal article
AN - SCOPUS:85079393691
SN - 0361-0926
VL - 50
SP - 4617
EP - 4638
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 19
ER -