| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000432944 |
| 005 | | 20200225105414 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781088374764 |
| 035 | |
▼a (MiAaPQ)AAI22589811 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 310 |
| 100 | 1 |
▼a Gitlin, Sergey. |
| 245 | 10 |
▼a Efficient Estimation with Smooth Penalization. |
| 260 | |
▼a [S.l.]:
▼b Northwestern University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 152 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B. |
| 500 | |
▼a Advisor: Horowitz, Joel |
| 502 | 1 |
▼a Thesis (Ph.D.)--Northwestern University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a This dissertation proposes an oracle efficient estimator in the context of a sparse linear model. Chapter 1 introduces the penalty and the estimator that optimizes a penalized least squares objective. Unlike existing methods, the penalty is differentiable - once, and hence the estimator does not engage in model selection. This feature allows the estimator to reduce bias relative to a popular oracle efficient method (SCAD) when small, but not insignificant, coefficients are present. Consequently the estimator delivers a lower realized squared error of coefficients of interest. Furthermore, the objective function with the proposed penalty is shown to be convex |
| 590 | |
▼a School code: 0163. |
| 650 | 4 |
▼a Economics. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0501 |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a Northwestern University.
▼b Economics. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-04B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0163 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493184
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |