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Finite Sample Bounds and Path Selection for Sequential Monte Carlo
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Marion, Joseph. |
| 단체저자명 | Duke University. Statistical Science. |
| 서명/저자사항 | Finite Sample Bounds and Path Selection for Sequential Monte Carlo. |
| 발행사항 | [S.l.] : Duke University., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 118 p. |
| 소장본 주기 | School code: 0066. |
| ISBN | 9780438377356 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B.
Adviser: Scott C. Schmidler. |
| 요약 | 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 |
| 요약 | 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 |
| 요약 | 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 |
| 요약 | 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 |
| 일반주제명 | Statistics. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International80-02B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14999681 |
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인쇄
| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00025527 | 310 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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