• 품질경영학회지
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• 제19권2호
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• pp.1-16
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• 1991

Recently, Cook and Weisberg(l989) presented dynamic graphics for regression diagnostics. They suggested animating graphics which could aid to understanding the effects of adding a variable to a model. In this paper, using the Cook and Weisberg's idea of animation, we propose a dynamic graphical method for residuals to display the effects of removing an observation from a model. Based on the information obtained from these animating graphics, it is possible to see the influence of outliers on influencial observations for regression diagnostics.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.21-32
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• 1997

Robust regression based on M-estimator reduces and/or bounds the influence of outliers in the y-direction only. Therefore, when several influential observations exist, diagnostics in the robust regression is required in order to detect them. In this paper, we propose influence diagnostics in the robust regression based on M-estimator and its one-step version. Noting that M-estimator can be obtained through iterative weighted least squares regression by using internal weights, we apply the weighted least squares (WLS) regression diagnostics to robust regression.

• 응용통계연구
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• 제10권2호
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• pp.241-251
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• 1997

기존의 회귀진단 방법은 자료의 구조를 변화시키거나 회귀모형의 형식을 변화시킬 때 이것이 잔차에 미치는 영향을 분석하는 것이 주를 이루었다. 그러나 역으로 잔차를 변화시킬 때 이것이 회귀모형에 미치는 영향을 분석하는 것을 생각할 수 있다. 이것은 현실적으로 몇 개의 특정한 자료에 더욱 가중치를 부여하여 회귀모형을 만들거나 또는 잔차의 패턴을 정상화하고자 할 때 유용한 방법이 될 수 있다. 본 연구팀은 기존의 회귀진단방법과 더불어 잔차패턴을 변화시킴으로서 회귀진단을 실시하는 방법을 동적그라픽스기법에 의해 회귀진단시스템(REgression Diagnostics System-REDS)으로 구현하였으며 본 논문을 통해 이를 소개하고자 한다.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.23-36
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• 2000

This paper discusses the local influence approach to the Weibull regression model with censored data. Diagnostics for the Weibull regression model are proposed and developed when simultaneous perturbations of the response vector are allowed.

• Journal of the Korean Data and Information Science Society
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• 제11권1호
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• pp.73-81
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• 2000

The variance inflation factor can be expressed by the square of the ratio of t-statistics associated with slopes of partial regression and partial residual plots. Disagreement of two sides in the interpretation can be occurred, and we analyze it with some illustrations.

• Communications for Statistical Applications and Methods
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• 제16권2호
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• pp.309-315
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• 2009

We extended the results of Roy and Guria (2008) to multiple deletions in logistic regression models. Since single deletions may not exactly detect outliers or influential observations due to swamping effects and masking effects, it needs multiple deletions. We developed conditional deletion diagnostics which are designed to overcome problems of masking effects. We derived the closed forms for several statistics in logistic regression models. They give useful diagnostics on the statistics.

• 응용통계연구
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• 제15권2호
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• pp.233-250
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• 2002

Cox의 비례위험모형(proportional hazards model)은 생존자료(survival data)에 대한 회귀모형으로 경제학 및 의·공학을 비롯한 여러 응용 분야에서 가장 널리 쓰이고 있는 모형 중 하나이다. 그러나, 이 모형은 일반선헝모형에 비해 잔차 분석을 통한 회귀 진단의 연구가 널리 알려져 있지 않아, 국내의 실제 자료 분석에서는 잔차 분석에 대한 활용이 거의 이루어지지 않고 있는 실정이다. 이에 본 논문에서는 그 동안 제안된 여러 잔차들을 비교 분석하고, S-plus 프로그램을 이용한 PBC(primary biliary cirrhosis) 자료분석을 통해 각 잔차들의 의미를 고찰하고자 한다.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제27권2호
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• pp.71-81
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• 2020

Multicollinearity is a common problem in linear regression models when two or more regressors are highly correlated, which yields some serious problems for the ordinary least square estimates of the parameters as well as model validation and interpretation. In this paper, first the problem of multicollinearity and its subsequent effects on the linear regression along with some important measures for detecting multicollinearity is reviewed, then the role of eigenvalues and eigenvectors in detecting multicollinearity are bolded. At the end a real data set is evaluated for which the fitted linear regression models is investigated for multicollinearity diagnostics.

• Journal of the Korean Statistical Society
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• 제19권2호
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• pp.151-159
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• 1990

Regression diagnostics often involves assesment of the changes that result from deleting multiple cases. Diagnostic mehtodology based on global influence measure, however, needs prohibitive computing time. As an alternative, Cook (1986) developed influence approach in which it is checked whether a minor modification of specifiation influences key results of an analysis. In line with Cook's development, we propose and study an inflence derivative method that yields both the magnitude and direction of case influences. The utility of our methodology is highlighted when case influence derivatives are plotted in a lower demensional space. Such plots are especially effective in unmasking "masked" observations in least squares regression and in robust regression also. We give several illustrations.strations.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.21-28
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• 1996

Collinearities contained in MEM cause the same problems as they do in traditional regression model, so the detection of collinearities is a crucial topic in MEM. One diagnostic was introduced by Carrillo-Gamboa and Gunst, but their method did not work in some cases. Two alternative collinearity diagnostics that provide reasonable measure of collinearities are proposed. Simulation study is performed to compare the small-sample properties of the proposed collinearity diagnostics.