• 대한예방의학회:학술대회논문집
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• 1999.10a
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• pp.179-180
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• 1999

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.103-110
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• 1999

In this paper, we summarize some relative risk estimators under the two sample model with proportional hazard and examine the relative efficiencies of the nonparametric estimators relative to the maximum likelihood estimator of a parametric survival function under random censoring model by comparing their asymptotic variances.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.816-817
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• 2013

본 논문은 전기자동차를 이용한 관광에 있어서 사용자가 선택한 목적지 집합에 대해 전기자동차 충전까지 고려하여 방문 순서를 결정하고 그 결과를 사용자 단말기 App을 통하여 보여주는 관광 스케줄러를 구현하였다. 스케줄링 엔진은 방문총거리가 짧으면서 충전대기시간을 최소화하기 위해 $A^*$ 알고리즘과 유전자 알고리즘으로 구현되었고 웹서비스 방식으로 단말기와 상호작용함으로써 서비스의 확장성과 편의성을 기한다.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.497-505
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• 2003

Under normality assumption, the tolerance interval for a future observation is sometimes of great interest in statistics. In this paper, we state the influence function on the standard deviation $\sigma$, and use it to derive the influence function on tolerance limits. Simulation study shows that the two influence functions perform very well.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.66-81
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• 1994

Several sample statistics to simultaneously monitor both means and variances for multivariate quality characteristics under multivariate normal process are proposed. Performances of multivariate Shewhart schemes and cumulative sum(CUSUM) schemes are evaluated for matched fixed sampling interval(FSI) and variable sampling interval(VSI) feature. Numerical results show that multivariate CUSUM charts are more efficient than Shewhart charts for small or moderate shifts and VSI feature is more efficient than FSI feature.

• Journal of the Korean Statistical Society
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• v.21 no.1
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• pp.70-79
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• 1992

The generalized linear models with random regrssors case are studied for bootstrapping. Only the natural link functions are considered. It is shown that the bootstrap approximation to the distribution of the maximum likelihood estimators is valid for almost all sample sequences. A slight extension of this model is also considered.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.13-17
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• 2005

In recent years, many people use R as a statistics system. R is frequently updated by many R project teams. We are interested in the method of multiple outlier detection and know that R is not supplied the method of multiple outlier detection. In this talk, we review these procedures for detecting multiple outliers and provide more efficient procedures combined with direct methods and indirect methods using R.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.13-15
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• 2005

In this paper, we propose an extension of the maximum likelihood seasonal cointegration procedure developed by Johansen and Schaumburg (1999) for daily time series. We presented the finite sample distribution of the associated rank test statistics for daily data.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.145-153
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• 1998

In this paper, a hierarchical Bayesian analysis of a bivariate exponential model is discussed using Gibbs sampler. Parameters and reliability estimators are obtained. A numerical study is provided.