| LDR | | 02226nmm uu200409 4500 |
| 001 | | 000000331200 |
| 005 | | 20240805163622 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438377356 |
| 035 | |
▼a (MiAaPQ)AAI10839504 |
| 035 | |
▼a (MiAaPQ)duke:14828 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 082 | 0 |
▼a 310 |
| 100 | 1 |
▼a Marion, Joseph. |
| 245 | 10 |
▼a Finite Sample Bounds and Path Selection for Sequential Monte Carlo. |
| 260 | |
▼a [S.l.] :
▼b Duke University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 118 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. |
| 500 | |
▼a Adviser: Scott C. Schmidler. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Duke University, 2018. |
| 520 | |
▼a Sequential Monte Carlo (SMC) samplers have received attention as an alternative to Markov chain Monte Carlo for Bayesian inference problems due to their strong empirical performance on difficult multimodal problems, natural synergy with parallel |
| 520 | |
▼a In this thesis, we provide conditions under which SMC provides a randomized approximation scheme, showing how to choose the number of of particles and Markov kernel transitions at each SMC step in order to ensure an accurate approximation with b |
| 520 | |
▼a A key advantage of this approach is that the bounds provide insight into the selection of efficient sequences of SMC distributions. When the target distribution is spherical Gaussian or log-concave, we show that judicious selection of interpolat |
| 520 | |
▼a Selecting efficient sequences of distributions is a problem that also arises in the estimation of normalizing constants using path sampling. In the final chapter of this thesis, we develop automatic methods for choosing sequences of distribution |
| 590 | |
▼a School code: 0066. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a Duke University.
▼b Statistical Science. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0066 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999681
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자 |