• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.635-642
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• 2005

In statistical diagnostics a large number of influence measures have been proposed for identifying outliers and influential observations. However it seems to be few accounts of the influence diagnostics on test statistics. We study influence analysis on the likelihood ratio test statistic whether the two sets of variables are uncorrelated with one another or not. The influence of observations is measured using the case-deletion approach, the influence function. We compared the proposed influence measures through two illustrative examples.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.841-849
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• 2001

The influence in fitting an equicorrelation model is investigated using the influence function. The influence functions for the model parameters are derived and its sample versions are used for investigating the influence of observations on the estimators of the parameters. Some relationships among the sample versions are found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model using the influence function method. An example is given for illustration.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2001년도 추계학술대회
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• pp.13-16
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• 2001

We compare methods for detecting influential observations that have a large influence on the likelihood ratio test statistics that the two sets of variables are uncorrelated with one another. For this purpose we derive results of the deletion diagnostic, the influence function, the standardized influence matrix and the local influence. An illustrative example is given.

• 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.

• 한국의류학회지
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• 제36권10호
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• pp.1074-1086
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• 2012

This study examines the influence of mentoring function on major adaptation of university students in a fashion related department and identifies the moderating role of self-efficacy and mentor competence on the effectiveness of a fashion mentoring function. Questionnaire data were gathered from 266 university students in a fashion related department with previous experience in a mentoring program. The results showed that the psychosocial function, sensitivity developmental function, and the fashion career developmental function had a positive impact on the department adaptation (adaptation for professor and adaptation for learning). In addition, there were moderating effects of self-efficacy on the influence of the fashion career developmental function on professor adaptation and the moderating effects of mentor competence on the influence of the sensitivity developmental function on professor adaptation. The results of this study provide various guidelines for professors or administrators of fashion related departments who are interested in mentoring systems.

• 응용통계연구
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• 제24권5호
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• pp.941-949
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• 2011

본 논문에서는 세 집단만을 판별분석 할 경우에 계산되는 오분류확률에 영향을 미치는 이상치 판별을 목적으로 하며, 쉽게 응용 가능한 간단한 영향함수식을 제시하였다. 그리고 제시된 수식을 이용하여 안면 데이터로 세 가지 사상체질을 분류해보고 각 관찰값들의 오분류확률에 대한 영향함수를 계산하였다. 이상치를 제거하고 재 판별분석을 하는 데 있어, 오분류확률에 대한 영향함수를 이용하는 것이 효율적인 방법임을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제21권3호
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• pp.213-224
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• 2014

In this paper, we study the problem of transforming to normality. We propose to estimate the transformation parameter by minimizing a weighted squared distance between the empirical characteristic function of transformed data and the characteristic function of the normal distribution. Our approach also allows for other symmetric target characteristic functions. Asymptotics are established for a random sample selected from an unknown distribution. The proofs show that the weight function $t^{-2}$ needs to be modified to have thinner tails. We also propose the method to compute the influence function for M-equation taking the form of U-statistics. The influence function calculations and a small Monte Carlo simulation show that our estimates are less sensitive to a few outliers than the maximum likelihood estimates.

• 수면정신생리
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• 제5권2호
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• pp.177-184
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• 1998

Objectives : Disturbance of sleep with or without sleep apnea may impair the memory function. Sleep deficiency, sleepiness, sleep apnea and emotional problem in sleep disorders can induce an impairment of memory function. Methods : In this study, the polysomnographies were administered to 58 sleep apnea patients and 38 sleep disorder patients without sleep apnea. Their clinical symptoms were quantitatively evaluated. Short term and long term memory were evaluated before and after polysom no graphy with Digit symbol test and Rey-Osterrieth complex figure test. And correlations among various sleep, repiratory and clinical variables were statistically studied in order to explore which variables may influence on memory function. Results and Conclusions : Results are as follows. Depth of sleep cis positively correlated with memory function. As sleep apnea increases and average saturation of blood oxygen decreases, memory function is more impaired. Emotional depression, high blood pressure, obesity or alcohol impaired memory function. However, daytime sleepiness was not significantly correlated with memory function. The possible mechanisms how above factors influence on the memory function were discussed.

• 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.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.305-317
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• 2003

We suggest methods to measure the changes in $x^2$ statistic when a row is deleted from a two-way contingency table. The influence function is extended and the deletion method is applied. Two examples are presented and we compare the results obtained from the influence function method and the deletion method.