• 응용통계연구
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• 제28권2호
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• pp.361-369
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• 2015

연속측도의 반응변수가 반복측정된 실험 자료의 분석을 위해 흔히 선형혼합모형이 사용된다. 그러나, 잔차의 분포가 이분산성이거나 비정규성을 가질 때 표준적인 선형혼합모형은 적절하지 않은 결과를 가져온다. 잔차의 분포가 두터운 꼬리를 가진 비정규분포를 보이는 타이어 필드시험 데이터를 로버스트 선형혼합모형에 적합시킴으로써 보다 더 정확하고 신뢰할 수 있는 분석결과를 얻을 수 있다. 추가적으로 신뢰성 분석 결과를 제시한다.

• 한국경영과학회지
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• 제40권3호
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• pp.39-48
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• 2015

Even though ruin probability is a fundamental value to determine the insurance premium and policy, the complexity involved in computing its exact value forced us resort to an approximate method. In this paper, we first present an exact method to compute ruin probability under the assumption that the claim size has a GPH distribution, Then, for the arbitrary claim size distribution, we provide a method computing ruin probability quite accurately by approximating the distribution as a GPH. The validity of the proposed method demonstrated by a numerical example. The GPH approach seems to be valid for heavy-tailed claims as well as usual light-tailed claims.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.197-201
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• 2005

In this article, we will compare the performance of the mean control chart, the median control chart, the transformed mean control chart, the transformed median control chart, and the precedence control chart by simulation study. For control charts with transformed data, Yeo-Johnson transformation is used. Under the in-control condition, ARL's in all control charts coincide with the designed ARL in the normal distribution, but in the other distributions, only the precedence control chart provides the in-control ARL as designed. Under the out-of-control condition, the mean control chart is preferred in the normal distribution and the median control chart is preferred in the heavy-tailed distribution and the precedence control chart outperforms in the short-tailed distribution.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.283-290
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• 1996

The simulation study shows that the rank transform test has relatively superior power advantages over the parametric analysis of variance test in many cases for a $2^3$ factorial design, particularly with heavy-tailed distributions of the error terms. However the rank transform test should be cautiously used when all main effects and interactions related to a testing effect are possibly present at the same time.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1309-1317
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• 2006

The paper considers some Bayes estimators of the finite population mean with auxiliary information under priors which are scale mixtures of normal, and thus have tail heavier than that of the normal. The proposed estimators are quite robust in general. Numerical methods of finding Bayes estimators under these heavy tailed priors are given, and are illustrated with an actual example.

• Journal of the Korean Statistical Society
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• 제33권2호
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• pp.149-157
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• 2004

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive processes to determine whether or not a time series is stationary. The proposed tests are robust to the outliers and the heteroscedastic errors, and they have an exact binomial null distribution regardless of the period of seasonality and types of median adjustments. A Monte-Carlo simulation shows that the sign test is locally more powerful than the tests based on ordinary least squares estimator (OLSE) for heavy-tailed and/or heteroscedastic error distributions.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.3-9
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• 2002

In financial time series, the autoregressive conditional heteroscedastic (ARCH) models have been widely used for modeling conditional variances. In many cases, non-normality or heavy-tailed distributions of the data have influenced the estimation methods under normality assumption. To solve this problem, a robust function for the conditional variances of the errors is proposed and compared the relative efficiencies of the estimators with other conventional models.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.281-286
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• 2003

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive process to determine whether or not a time series is stationary. The tests have an exact binomial null distribution and are robust to the outliers and the heteroscedastic errors. Monte-Carlo simulation shows that the sign test is locally more powerful than the OLSE-based tests for heavy-tailed and/or heteroscedastic error distributions.

• Journal of the Korean Statistical Society
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• 제36권3호
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• pp.387-395
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• 2007

We propose a doubly robustified estimating function for the estimation of parameters in the context of ARCH models. We investigate asymptotic properties of estimators obtained as solutions of robust estimating equations. A simulation study shows that robust estimator from specified doubly robustified estimating equation provides better performance than conventional robust estimators especially under heavy-tailed distributions of innovation errors.

• 품질경영학회지
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• 제19권1호
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• pp.51-64
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• 1991

This paper deals with a robust subset selection procedure based on Hodges-Lehmann estimators of location parameters. An improved formula for the estimated standard error of Hodges-Lehmann estimators is considered. Also, the degrees of freedom of the studentized Hodges-Lehmann estimators are investigated and it is suggested to use 0.8n instead of n-1. The proposed procedure is compared with the other subset selection procedures and it is shown to have good effciency for heavy-tailed distributions.