(A) stepwise approach for the detection of influential observations in linear regression model = 선형 회귀 모형에 영향을 주는 관측치를 단계적으로 탐지하는 방법에 관한 연구

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In the statistical literature on regression analysis, much attention has been given to problems of detecting observations which, individually or jointly, exert a disproportionate influence on the outcome of linear regression analysis and to problems of assessing the influence of such cases. Most approaches are ways of measuring the change in some feature of analysis on the deletion of one or more observations. Various measures have been proposed which emphasize different aspects of influence on the linear regression. Among them the influence measure, $\mbox{C_m(X(d_m)X(d_m),\;\; ps^2(d_m}$)), proposed by Cook and Weisberg (1982) is mainly treated in this thesis. This measure will be called Cook-Weisberg measure in this thesis. This thesis is written with the intention of fulfilling four needs for Cook-Weisberg measure. First, even though Cook-Weisberg measure was proposed in 1982, an appropriate critical point has not been given. A critical point is suggested for the measure under the normality assumption. Second, an easy computational form of the measure is derived. Third, when computing the measure in practical problem, an efficient computational procedure is proposed. Fourth, programs are implemented which compute the influence measure with the stepwise approach.
Advisors
Kim, Byung-Chunresearcher김병천researcher
Description
한국과학기술원 : 수학과(전산통계전공),
Publisher
한국과학기술원
Issue Date
1994
Identifier
68920/325007 / 000895831
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 수학과(전산통계전공), 1994.2, [ iii, 56 p. ; ]

URI
http://hdl.handle.net/10203/41768
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=68920&flag=dissertation
Appears in Collection
MA-Theses_Ph.D.(박사논문)
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