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020 ▼a 9780438348400
035 ▼a (MiAaPQ)AAI10829662
035 ▼a (MiAaPQ)unc:17953
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 310
1001 ▼a Jiang, Meilei.
24510 ▼a Statistical Learning of Integrative Analysis.
260 ▼a [S.l.] : ▼b The University of North Carolina at Chapel Hill., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 138 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Advisers: J. S. Marron
5021 ▼a Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2018.
520 ▼a Integrative analysis is of great interest in modern scientific research. This dissertation mainly focuses on developing new statistical methods for integrative analysis.
520 ▼a We first discuss a clustering analysis of a microbiome dataset in combination with phylogenetic information. Discovering disease related pneumotypes of the infected lower lung is difficult because the lower lung typically has few species of micr
520 ▼a In the second part, we discuss an integrative analysis of disparate data blocks measured on a common set of experimental subjects. We introduce Angle-Based Joint and Individual Variation Explained (AJIVE) capturing both joint and individual vari
520 ▼a In the third part, we introduce a new perturbation framework, which estimates the angle between an arbitrary given direction and the underlying signal spaces. We also propose an efficient data-driven bootstrap procedure to compute this angle. Wh
590 ▼a School code: 0153.
650 4 ▼a Statistics.
650 4 ▼a Mathematics.
690 ▼a 0463
690 ▼a 0405
71020 ▼a The University of North Carolina at Chapel Hill. ▼b Statistics and Operations Research.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0153
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999331 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자