• 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.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.229-239
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• 2007

We present a diagnostic method for the quasi-likelihood estimators in generalized linear models. Since these estimators can be usually obtained by iteratively reweighted least squares which are well known to be very sensitive to unusual data, a diagnostic step is indispensable to analysis of data. We extend the local influence approach based on the maximum likelihood function to that on the quasi-likelihood function. Under several perturbation schemes local influence diagnostics are derived. An illustrative example is given and we compare the results provided by local influence and deletion.

• Journal of the Korean Statistical Society
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• 제33권2호
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• pp.233-244
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• 2004

The influence of observations is investigated in fitting proportional covariance matrices model. Local influence measures are obtained when all parameters or subsets of the parameters are of interest. We will also derive the local influence measure for investigating the influence of observations in testing the proportionality of covariance matrices. A numerical example is given for illustration.

• Journal of the Korean Statistical Society
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• 제31권4호
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• pp.447-458
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• 2002

The influence of observations in the equicorrelation model is investigated using the local influence approach when all parameters or subsets of parameters are of interest. When a parameter of interest is scalar, an analytical form of the local influence measure can be found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model. An example is given for illustration.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.479-485
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• 2003

The influence of observations on the Wilks' lambda test of a linear hypothesis in multivariate regression is investigated using the local influence method. The perturbation scheme of case-weights is considered. A numerical example is given to show the effectiveness of the local influence method in identifying the influential observations.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.465-474
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• 2015

In this paper, we study the local influence analysis of LIU type estimator in the linear mixed models. Using the method proposed by Shi (1997), the local influence of LIU type estimator in three disturbance models are investigated respectively. Furthermore, we give the generalized Cook's distance to assess the influence, and illustrate the efficiency of the proposed method by example.

• Journal of the Korean Statistical Society
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• 제25권1호
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• pp.145-151
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• 1996

The local behaviour of the surface formed by the perturbed maximum likelihood estimator of the squared Mahalanobis distance is investigated. The study of the local behaviour allows a simultaneous perturbation on the samples of interest and it is effective in identifying influential observations.

• Journal of applied mathematics & informatics
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• 제5권2호
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• pp.489-498
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• 1998

The influence of observations the on the goodness-of-fit test in maximum likelihood factor analysis is investigated by using the local influence method. under an appropriate perturbation the test statistic forms a surface. One of main diagnostics is the maximum slope of the perturbed surface the other is the direction vector cor-responding to the curvature. These influence measures provide the information about jointly influence measures provide the information about jointly influential observations as well as individ-ually influential observations.

• Communications for Statistical Applications and Methods
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• 제13권2호
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• pp.267-272
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• 2006

A procedure for selecting regressors in the linear regression model is suggested using local influence approach. Under an appropriate perturbation scheme, the effect of perturbation of regressors on the profile log-likelihood displacement is assessed for variable selection. A numerical example is provided for illustration.

• 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.