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High-dimensional Regression Models with Structured Coefficients
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Li, Yuan. |
| 단체저자명 | The University of Wisconsin - Madison. Statistics. |
| 서명/저자사항 | High-dimensional Regression Models with Structured Coefficients. |
| 발행사항 | [S.l.] : The University of Wisconsin - Madison., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 124 p. |
| 소장본 주기 | School code: 0262. |
| ISBN | 9780438298781 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Garvesh Raskutti. |
| 요약 | Regression models are very common for statistical inference, especially linear regression models with Gaussian noise. But in many modern scientific applications with large-scale datasets, the number of samples is small relative to the number of |
| 요약 | Firstly, most literature provides statistical analysis for high-dimensional linear models with Gaussian noise, it is unclear whether similar results still hold if we are no longer in the Gaussian setting. To answer this question under Poisson se |
| 요약 | Secondly, much of the theory and methodology for high-dimensional linear regression models are based on the assumption that independent variables are independent of each other or have weak correlations. But it is possible that this assumption is |
| 일반주제명 | Statistics. Mathematics. Computer science. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-12B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T15001016 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00025921 | DP 310 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출불가(별치) |
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