(A) method for regression splines in least squares approach최소 제곱법에 있어서의 회귀스플라인에 대한 방법
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Kim, Byung-Chun | - |
| dc.contributor.advisor | 김병천 | - |
| dc.contributor.author | Ro, Seung-Gye | - |
| dc.contributor.author | 노승계 | - |
| dc.date.accessioned | 2011-12-14T04:58:08Z | - |
| dc.date.available | 2011-12-14T04:58:08Z | - |
| dc.date.issued | 1988 | - |
| dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=66080&flag=dissertation | - |
| dc.identifier.uri | http://hdl.handle.net/10203/42303 | - |
| dc.description | 학위논문(석사) - 한국과학기술원 : 응용수학과, 1988.2, [ [ii], 30 p. ; ] | - |
| dc.description.abstract | In this paper, we find a necessary and sufficient condition of $\beta=0$ in the model (2.1.1) and offer its proof. Also we suggest the procedure, say BEP, selecting the "best" regression equation, which is a modification of the backward elimination procedure in the variable selection, and shows the composite phenomena resulting from a polynomial regression model and the backward elimination procedure. | eng |
| dc.language | eng | - |
| dc.publisher | 한국과학기술원 | - |
| dc.title | (A) method for regression splines in least squares approach | - |
| dc.title.alternative | 최소 제곱법에 있어서의 회귀스플라인에 대한 방법 | - |
| dc.type | Thesis(Master) | - |
| dc.identifier.CNRN | 66080/325007 | - |
| dc.description.department | 한국과학기술원 : 응용수학과, | - |
| dc.identifier.uid | 000861127 | - |
| dc.contributor.localauthor | Kim, Byung-Chun | - |
| dc.contributor.localauthor | 김병천 | - |
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