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020 ▼a 9780438036420
035 ▼a (MiAaPQ)AAI10787591
035 ▼a (MiAaPQ)upenngdas:13166
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 310
1001 ▼a Deshpande, Sameer K.
24510 ▼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.
5021 ▼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
71020 ▼a University of Pennsylvania. ▼b Statistics.
7730 ▼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
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997402 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자