• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.495-506
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• 1995

We present formula for detecting influential observations on the smoothing parameter in smoothing spline. Further, we express them as functions of basic building blocks such as residuals and leverage, and compare it with the local influence approach by Thomas (1991). An example based on a real data set is given.

• 응용통계연구
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• 제31권1호
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• pp.97-108
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• 2018

회귀모형을 이용하여 자료를 분석하는 경우 이상점이나 영향점의 유무를 검정하는 회귀진단기법은 모형의 적합성을 체크하기 위한 필수적인 도구이다. 이러한 이상점이나 영향점이 존재하는 경우 회귀분석의 결과가 왜곡되어 해석이 된다. Jang과 Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014)은 불꽃그림이란 이름을 붙인 그래픽 방법를 제시하였는데 관측값에 부여된 가중치를 1에서 0으로 변화함에 따라 이상점이나 영향점이 회귀계수 및 잔차제곱합에 어떠한 영향을 미치는지 살펴 보았다. 본 연구에서는 다반응 반응표면분석에서 이러한 불꽃그림을 적용하여 보고자 한다.

• Journal of the Korean Statistical Society
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• 제27권4호
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• pp.471-483
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• 1998

The influence of observations on the misclassification probability in multiple discriminant analysis under the equal covariance assumption is investigated by the local influence method. Under an appropriate perturbation we can get information about influential observations and outliers by studying the curvatures and the associated direction vectors of the perturbation-formed surface of the misclassification probability. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. An illustrative example is given for the effectiveness of the local influence method.

• 품질경영학회지
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• 제28권1호
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• pp.119-131
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• 2000

This paper suggests a new diagnostic measure for detecting influential observations in linear discriminant analysis (LDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the imaginary training sample methodology. The Bayes factor is taken as a criterion for testing homogeneity of covariance matrices in LDA model. It is noted that the effect of an observation over the criterion is fully explained by the diagnostic measure. We suggest a graphical method that can be taken as a tool for interpreting the diagnostic measure and detecting influential observations. Performance of the measure is examined through an illustrative example.

• 응용통계연구
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• 제13권2호
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• pp.383-392
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• 2000

1970년대 후반부터 영향력이 있는 관측값을 검출하기 위해서 회귀분석을 포함한 다양한 다변량 해석법에서의 영향분석 및 감도분석에 대한 연구가 진행되어 왔다. 결손 값이 포함된 불완전한 자료에 관해서도 이러한 연구가 필요하다. 이와 관련하여 Kim et al.(1998)등은 평균벡터와 분산공분산행렬에 대한 최우추정값에 초점을 두고 불완전한 자료에 대한 다변량 해석법에서의 감도분석에 관한 방법적 연구를 다루었다. Kim et al.(1998)에서는 Cook’s D 통계량을 이용하였으나, 본 논문에서는 결손값이 있는 다변량 자료에 대해서 주성분을 이용하여 영향력이 있는 관측값을 검출하는 방법에 대해서 살펴보았다. 이 때, 결손값은 EM알고리즘에 의해 대치하여 PCA 통계량을 유도하였다.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.939-946
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• 1999

We propose methods for detecting influential observations that have a large influence on the likelihood ratio test statistic for the multivariate Behrens-Fisher problem. For this purpose we derive the influence curve and the derivative influence of the likelihood ratio test statistic. An illustrative example is given to show the effectiveness of the proposed methods on the identification of influential observations.

• Communications for Statistical Applications and Methods
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• 제4권2호
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• pp.359-365
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• 1997

Unusual observations can greatly influence the results of least wquares estimation. I propose graphical methods which can detect the influential observations.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.317-324
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• 2017

An influence measure known as Cook's distance has been used for judging the influence of each observation on the least squares estimate of the parameter vector. The distance does not reflect the distributional property of the change in the least squares estimator of the regression coefficients due to case deletions: the distribution has a covariance matrix of rank one and thus it has a support set determined by a line in the multidimensional Euclidean space. As a result, the use of Cook's distance may fail to correctly provide information about influential observations, and we study some reasons for the failure. Three illustrative examples will be provided, in which the use of Cook's distance fails to give the right information about influential observations or it provides the right information about the most influential observation. We will seek some reasons for the wrong or right provision of information.

• 응용통계연구
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• 제31권1호
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• pp.155-165
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• 2018

특이점 및 영향점은 자료분석을 하는 데 사용되는 수치적 측도들을 왜곡한다. 각종 자료분석에 있어서의 특이점 검색을 위한 검정 통계량이나 그림도구에 관한 연구는 꾸준히 전개되어 왔다. Jang과 Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014)은 불꽃그림이란 이름을 붙인 그림도구를 발표하였는데 특이점이나 영향점이 일변량/이변량 자료분석 및 회귀분석에 어떠한 영향을 미치는지 알기 위하여 3-D 불꽃그림 및 불꽃그림 행렬을 제시하였다. 본 연구에서는 이러한 불꽃그림이 통계적 추론에서 특이점을 찾아내고 이러한 특이점의 영향을 평가하기 위한 탐색적 자료분석 그림도구로서 사용될 수 있음을 보였다.

• Communications for Statistical Applications and Methods
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• 제20권3호
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• pp.217-223
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• 2013

Two influence diagnostic methods for the common mean model are proposed. First, an investigation of the influence of observations according to minor perturbations of the common mean model is made by adapting the local influence method which is based on the likelihood displacement. It is well known that the maximum likelihood estimates are in general sensitive to influential observations. Case-deletions can be a candidate for detecting influential observations. However, the maximum likelihood estimators are iteratively computed and therefore case-deletions involve an enormous amount of computations. An approximation by Newton's method to the maximum likelihood estimator obtained after a single observation was deleted can reduce much of computational burden, which will be treated in this work. A numerical example is given for illustration and it shows that the proposed diagnostic methods can be useful tools.