| LDR | | 01534nam u200373 4500 |
| 001 | | 000000420715 |
| 005 | | 20190215164709 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438036420 |
| 035 | |
▼a (MiAaPQ)AAI10787591 |
| 035 | |
▼a (MiAaPQ)upenngdas:13166 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 310 |
| 100 | 1 |
▼a Deshpande, Sameer K. |
| 245 | 10 |
▼a Bayesian Model Selection and Estimation without MCMC. |
| 260 | |
▼a [S.l.]:
▼b University of Pennsylvania.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 120 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Edward I. George. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Pennsylvania, 2018. |
| 520 | |
▼a This dissertation explores Bayesian model selection and estimation in settings where the model space is too vast to rely on Markov Chain Monte Carlo for posterior calculation. First, we consider the problem of sparse multivariate linear regressi |
| 590 | |
▼a School code: 0175. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a University of Pennsylvania.
▼b Statistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0175 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997402
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |