Probability density estimation approach in linear regression확률 밀도 추정을 이용한 선형 회귀 분석

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dc.contributor.advisorKim, Byung-Chun-
dc.contributor.advisor김병천-
dc.contributor.authorChi, Sang-Mun-
dc.contributor.author지상문-
dc.date.accessioned2011-12-14T04:59:08Z-
dc.date.available2011-12-14T04:59:08Z-
dc.date.issued1993-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=68340&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/42368-
dc.description학위논문(석사) - 한국과학기술원 : 수학과 전산통계 전공, 1993.2, [ [ii], 34, [2] p. ]-
dc.description.abstractThe purpose of this paper is to study the linear relation between the variable x and y. The proposed method determines the best-fitting line using a probability density estimation. It is shown that the method reduced to least-squares method as the bandwidth is increased and that the line which contains data points more than any other lines do is a best-fitting line as bandwidth is decreased. Also, we have shown that the method is insensitive to a few egregious error in the dependent variable as bandwidth is choosed appropriatly. Consequently, the new method gives a various altemative interpretation of the data as bandwidth varies.eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.titleProbability density estimation approach in linear regression-
dc.title.alternative확률 밀도 추정을 이용한 선형 회귀 분석-
dc.typeThesis(Master)-
dc.identifier.CNRN68340/325007-
dc.description.department한국과학기술원 : 수학과 전산통계 전공, -
dc.identifier.uid000911577-
dc.contributor.localauthorKim, Byung-Chun-
dc.contributor.localauthor김병천-
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