| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000330519 |
| 005 | | 20241101095808 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438354128 |
| 035 | |
▼a (MiAaPQ)AAI10846106 |
| 035 | |
▼a (MiAaPQ)umn:19537 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 310 |
| 100 | 1 |
▼a O'Connell, Michael J. |
| 245 | 10 |
▼a Integrative Analyses for Multi-Source Data with Multiple Shared Dimensions. |
| 260 | |
▼a [S.l.] :
▼b University of Minnesota.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 96 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
| 500 | |
▼a Adviser: Eric F. Lock. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Minnesota, 2018. |
| 520 | |
▼a High dimensional data consists of matrices with a large number of features and is common across many fields of study, including genetics, imaging, and toxicology. This type of data is challenging to analyze because of its size, and many traditio |
| 590 | |
▼a School code: 0130. |
| 650 | 4 |
▼a Statistics. |
| 650 | 4 |
▼a Public health. |
| 650 | 4 |
▼a Genetics. |
| 690 | |
▼a 0463 |
| 690 | |
▼a 0573 |
| 690 | |
▼a 0369 |
| 710 | 20 |
▼a University of Minnesota.
▼b Biostatistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0130 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000111
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |