Estimating the number of equal components for two high-dimensional mean vectors
| dc.contributor.author | Yu, Wei | |
| dc.contributor.author | Zhu, Lixing | |
| dc.contributor.author | Xu, Wangli | |
| dc.contributor.researchID | 37214675 - Zhu, Lixing | |
| dc.date.accessioned | 2020-03-12T11:56:04Z | |
| dc.date.available | 2020-03-12T11:56:04Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | In this article, we propose a new method for estimating the number of equal components m0 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 m0 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 | en_US |
| dc.identifier.citation | Yu, W. et al. 2020. Estimating the number of equal components for two high-dimensional mean vectors. Communications in statistics: theory and methods, (In press). [https://doi.org/10.1080/03610926.2020.1722842] | en_US |
| dc.identifier.issn | 0361-0926 | |
| dc.identifier.issn | 1532-415X (Online) | |
| dc.identifier.uri | http://hdl.handle.net/10394/34340 | |
| dc.identifier.uri | https://www.tandfonline.com/doi/full/10.1080/03610926.2020.1722842 | |
| dc.identifier.uri | https://doi.org/10.1080/03610926.2020.1722842 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor and Francis | en_US |
| dc.subject | Multiple hypothesis testing | en_US |
| dc.subject | High-dimensional data | en_US |
| dc.subject | DNA microarray analysis | en_US |
| dc.subject | False discovery rate | en_US |
| dc.title | Estimating the number of equal components for two high-dimensional mean vectors | en_US |
| dc.type | Article | en_US |
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