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last version of thesis 1.pdf (399.78 KB)
ETD Abstract Container
Abstract Header
RECOVERING SPARSE DIFFERENCES BETWEEN TWO HIGH-DIMENSIONAL COVARIANCE MATRICES
Author Info
ALHARBI, YOUSEF S
ORCID® Identifier
http://orcid.org/0000-0003-3590-5822
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=kent1500392318023941
Abstract Details
Year and Degree
2017, MS, Kent State University, College of Arts and Sciences / Department of Mathematical Sciences.
Abstract
Recovering sparse differences between two high-dimensional covariance matrices has been an important research topic. This topic has the workable application of comparing the dependence among the measurements of the genes subject to different treatments. This thesis proposes a new approach for recovering the sparse differences between two high-dimensional covariance matrices. The proposed method can control the false discovery rate (FDR) at any pre-selected significance level. At the same time, it can reduce the false non-discovery rate (FNR) by utilizing data dependence. An algorithm for implementing the approach is also provided. Simulation studies are conducted to demonstrate the numerical performance of the method.
Committee
Jun Li, Prof. (Advisor)
Omar De la Cruz, Prof. (Committee Member)
Xiaoyu Zheng, Prof. (Committee Member)
Pages
22 p.
Subject Headings
Mathematics
;
Statistics
Keywords
covariance matrices, sparse, false discovery rate
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Citations
ALHARBI, Y. S. (2017).
RECOVERING SPARSE DIFFERENCES BETWEEN TWO HIGH-DIMENSIONAL COVARIANCE MATRICES
[Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1500392318023941
APA Style (7th edition)
ALHARBI, YOUSEF.
RECOVERING SPARSE DIFFERENCES BETWEEN TWO HIGH-DIMENSIONAL COVARIANCE MATRICES.
2017. Kent State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=kent1500392318023941.
MLA Style (8th edition)
ALHARBI, YOUSEF. "RECOVERING SPARSE DIFFERENCES BETWEEN TWO HIGH-DIMENSIONAL COVARIANCE MATRICES." Master's thesis, Kent State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1500392318023941
Chicago Manual of Style (17th edition)
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Document number:
kent1500392318023941
Download Count:
272
Copyright Info
© 2017, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.