• 응용통계연구
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• 제2권2호
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• pp.47-51
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• 1989

단계별 회귀 분석법을 사용하여 환경 및 대기 오염이 암에 의한 사망률에 미치는 영향을 연구하였다. 또한 $SO_2$와 흡연도 암 사망률에 대한 중요한 요소라는 것을 보였다.

• Journal of applied mathematics & informatics
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• 제26권3_4호
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• pp.679-688
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• 2008

In multivariate regression analysis there exist many influence measures on the regression estimates. However it seems to be few of influence diagnostics on test statistics in hypothesis testing. Case-deletion approach is fundamental for investigating influence of observations on estimates or statistics. Tang and Fung (1997) derived single case-deletion of the Wilks' ratio, Lawley-Hotelling trace, Pillai's trace for testing a general linear hypothesis of the regression coefficients in multivariate regression. In this paper we derived more extended form of those measures to deal with joint influence among observations. A numerical example is given to illustrate the effect of joint influence on the test statistics.

• Asian Pacific Journal of Cancer Prevention
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• 제14권5호
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• pp.2805-2809
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• 2013

Objective: This study aimed at investigating whether the orphan nuclear receptor NR4A2 is significantly associated with clinicopathologic features and overall survival of patients with nasopharyngeal carcinoma (NPC). Methods: Immunohistochemistry was performed to determine NR4A2 protein expression in 84 NPC tissues and 20 non-cancerous nasopharyngeal (NP) tissues. The prognostic significance of NR4A2 protein expression was evaluated using Cox proportional hazards regression models and Kaplan-Meier survival analysis. Results: We did not find a significant association between total NR4A2 expression and clinicopathological variables in 84 patients with NPC. However, we observed that high cytoplasmic expression of NR4A2 was significantly associated with tumor size (T classification) (P = 0.006), lymph node metastasis (N classification) (P = 0.002) and clinical stage (P = 0.017). Patients with higher cytoplasmic NR4A2 expression had a significantly lower survival rate than those with lower cytoplasmic NR4A2 expression (P = 0.004). Multivariate Cox regression analysis analysis suggested that the level of cytoplasmic NR4A2 expression was an independent prognostic indicator for overall survival of patients with NPC (P = 0.033). Conclusions: High cytoplasmic expression of NR4A2 is a potential unfavorable prognostic factor for patients with NPC.

• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.575-582
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• 2019

The problem of selecting variables in the presence of outliers is considered. Variable selection and outlier detection are not separable problems because each observation affects the fitted regression equation differently and has a different influence on each variable. We suggest a simultaneous method for variable selection and outlier detection in a linear regression model. The suggested procedure uses a sequential method to detect outliers and uses all possible subset regressions for model selections. A simplified version of the procedure is also proposed to reduce the computational burden. The procedures are compared to other variable selection methods using real data sets known to contain outliers. Examples show that the proposed procedures are effective and superior to robust algorithms in selecting the best model.

• Communications for Statistical Applications and Methods
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• 제23권3호
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• pp.231-239
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• 2016

A graphical diagnostic method based on multiple case deletions in a regression context is introduced by using the sampling distribution of the difference between two least squares estimators with and without multiple cases. Principal components analysis plays a key role in deriving this diagnostic method. Multiple case deletions of test statistic are also considered when a new observation is fitted to a given regression model. The result is useful for detecting influential observations in econometric data analysis, for example in checking whether the consumption pattern at a later time is the same as the one found before or not, as well as for investigating the influence of cases in the usual regression model. An illustrative example is given.

• 응용통계연구
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• 제4권2호
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• pp.195-207
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• 1991

1986년 Cook 이 발표한 Local Influence Approach란 방법을 이용하여 최적 실험계획법에서 일반적으로 가정하는 등분산가정에 대한 민감도 분석을 수행할 수 있는 진단방법을 연구하 였다. D-최적계획법의 갖고 있는 제약조건을 부분적으로 완화시킬 수 있는 방안을 모색하 여 몇가지 예들에 적용시켜 보았다. 결론 및 이 방법에 대한 향후 연구과제에 대한 토의를 마지막절에 첨부하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.932-937
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• 2003

When oil pressure of damper is lost or relative stiffness of spring drops in vibration system, it can be fatally dangerous situation. A fault diagnosis method for vibration system using Support Vector Machine(SVM)is suggested in the paper. SVM is used to classify input data or applied to function regression. System status can be classified by judging input data based on optimal separable hyperplane obtained using SVM which learns normal and abnormal status. It is learned from the relationship of system state variables in term of spring, mass and damper. Normal and abnormal status are learned using phase plane as in put space, then the learned SVM is used to construct algorithm to predict the system status quantitatively

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• 품질경영학회지
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• 제28권2호
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• pp.57-69
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• 2000

This paper discusses the local influence approach to the linear regression models with AR(2) errors. Diagnostics for the linear regression models with AR(2) errors are proposed and developed when simultaneous perturbations of the response vector are allowed- That is, the direction of maximum curvature of local influence analysis is obtained by studying the curvature of a surface associated with the overall discrepancy measure.

• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.111-118
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• 2002

We study the influence of observations on testing a linear hypothesis using single and multiple case-deletions. The change in the F-test statistic due to case-deletions is shown to be completely determined by two externally Studentized residuals. These residuals we used for investigating the outlyingness when there are linear constraints or not. An illustrative example is given. It shows the usefulness of case-deletions.