• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.237-246
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• 2012

Bayesian methods have been recently used to identify multiple change-points. However, the studies for small data are limited. This paper suggests the Bayesian noncentral t distribution change-point model for small data, and applies the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model. Numerical results of simulation and real data show the performance of the new model in terms of the quality of the resulting estimation of the numbers and positions of change-points for small data.

• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.85-110
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• 2015

The purpose of this paper is to show the clustering trend and the empirical comparison and to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the Fuzzy(Average Index Transformation) DEA and Cross-efficiency models for 38 Asian ports during 11 years(2001-2011) with 4 input variables(birth length, depth, total area, and number of crane) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, clustering results by using Fuzzy(AIT)DEA show that 3 Korean ports[Busan(56.29%), Incheon(57.96%), and Gwangyang(66.80%) each]can increase the efficiency. Second, according to Cross-efficiency model, Busan(Hongkong, Kobe, Manila, Singapore, and Kaosiung etc.), Incheon(Aquaba, Dammam, Karachi, Mohammad Byin Oasim and Davao), and Gwangyang(Damman, Yokohama, Nogoya, Keelong, Kaosiung, and Bangkok) should be clustered with those ports in parentheses. Third, when both Fuzzy(AIT)DEA and Cross-efficiency models are mixed, the empirical result shows that 3 Korean ports[Busan(71.38%), Incheon(103.89%), and Gwangyang(168.55%) each]can increase the efficiency. The efficiency ranking comparison among the three models by using Wilcoxon Signed-rank Test was matched with the average level of 66%-67%. The policy implication of this paper is that Korean port policy planner should introduce the Fuzzy(AIT)DEA, and Cross-efficiency models with the mixed two models when clustering is needed among the Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT analysis among the clustering ports should be considered.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.713-722
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• 2020

Contrasted with the standard symmetric GARCH models, we consider a broad class of threshold-asymmetric models to analyse financial time series exhibiting asymmetric volatility. By further introducing power transformations, we add more flexibilities to the asymmetric class, thereby leading to power transformed and asymmetric volatility models. In particular, the paper is concerned with the nonstationary volatilities in which conditions for integrated volatility and explosive volatility are separately discussed. Dow Jones Industrial Average is analysed for illustration.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.789-794
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• 2005

LDA (Linear Discriminant Analysis) provides the projection that discriminates the data well, and shows a very good performance for face recognition. However, since LDA provides only one transformation matrix over whole data, it is not sufficient to discriminate the complex data consisting of many classes like honan faces. To overcome this weakness, we propose a new face recognition method, called LDA mixture model, that the set of alf classes are partitioned into several clusters and we get a transformation matrix for each cluster. This detailed representation will improve the classification performance greatly. In the simulation of face recognition, LDA mixture model outperforms PCA, LDA, and PCA mixture model in terms of classification performance.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.111-120
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• 2006

In a two-stage two-level balanced nested design, type I error rates for the parametric tests and the rank transformed tests for the main effects and the nested effects are in overall similar to each other. Furthermore, powers for the rank transformed statistic for the main effects and the nested effects in a two-stage two-level balanced nested design are generally superior to powers for the parametric statistic When the effect size and the sample size are increased, we can find that powers increase for the parametric statistic and the rank transformed statistic are dramatically improved. Especially for the case of the fixed effects in the asymmetric distributions such as an exponential distribution, powers for the rank transformed tests are quite high rather than powers for the parametric tests.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1195-1205
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• 2014

Compared with single design, powers of rank transformed statistic for testing main and interaction effects for $2{\times}2$ factorial in $4{\times}4$ latin square design are rapidly increased as effect size and replication size are increased. In general powers of rank transformed statistic are superior without regard to the diversified effect composition and the type of error distributions as nontesting factors are few and effect size are small. Powers of rank transformed statistic show much higher level than those of parametric statistic in exponential and double exponential distributions. Further powers of rank transformed statistic are very similar with those of parametric statistic in normal and uniform distributions.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.85-97
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• 1998

완전확률화모형 및 랜덤화블럭모형하에서의 주요한 다중비교 분석기법들을 시뮬레이션을 이용하여 검토하고자 하였다. 시뮬레이션 결과는 순위변환과 최소유의차검정을 이용한 다중비교 분석기법이 모수적 ANOVA F 검정과 Fisher의 유의차검정, 비모수적 Kruskal-Wallis 검정과 최소유의차검정 및 Friedman 검정과 최소유의차검정을 이용한 분석기법보다 전체실험오차율, 전체실험검정력 및 개별쌍검정력 면에서 상대적으로 뛰어남을 보여준다. 즉 순위변환한 ANOVA F 검정의 전체실험오차율은 명목상의 유의수준을 잘 유지하고 있으며, 전체실험검정력 및 개별쌍검정력은 모수적 ANOVA F 검정과 Kruskal-Wallis 검정 및 Friedman 검정기법보다 전반적으로 우수함을 알 수 있다.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.511-527
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• 2015

For time series analysis, power transformation (especially log-transformation) is widely used for variance stabilization or normalization for stationary ARMA(p, q) model. A simple and naive back transformed forecast is obtained by taking the inverse function of expectation. However, this back transformed forecast has a bias. Under the assumption that the log-transformed data is normally distributed. The unbiased back transformed forecast can be obtained by the expectation of log-normal distribution; consequently, the property of this back transformation was studied by Granger and Newbold (1976). We investigate the sensitivity of back transformed forecasts under several different underlying distributions using simulation studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.144-144
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• 2012

하천 제방의 안정성을 평가하기 위해서는 홍수시 제방 주변의 흐름특성을 분석하는 것이 필요하다. 일반적으로 홍수시 유속은 측정된 홍수량을 이용한 단면평균유속을 이용하여 평가를 하고 있기 때문에 제방 주변의 흐름특성을 정확하게 분석하는데 한계가 있다. 이를 개선하기 위해서는 홍수시 제방 주변의 유속을 측정하여야 하는데 접근이 어렵고 위험하기 때문에 봉부자 또는 유속계를 이용한 유속측정이 어려운 실정이다. 이와 같은 경우 제방 주변의 영상 분석을 이용한 표면영상유속계의 활용이 좋은 대안이 될 수 있다. 표면영상유속계의 경우 원거리에서도 줌을 이용하여 영상을 획득할 수 있고, 측정 시간이 짧기 때문에 제방 주변의 유속을 간편하게 측정 가능하다. 하지만 표면영상유속계(SIV)는 영상좌표와 물리좌표 사이의 좌표 변환을 필요로 한다. 종전까지는 일반적으로 8-변수 좌표 변환법이 널리 이용되었으나, 이 방법은 최소한 4점 이상의 참조점이 필요하기 때문에 수면위에 참조점을 설치해야 하는 어려움이 있다. 또한, 내삽을 하는 방법이기 때문에 참조점 내부의 점에 대해서는 비교적 정확한 변환이 가능하지만, 참조점 외부의 좌표들에 대해서는 부정확한 변환이 되는 단점이 있었다. 따라서 본 연구에서는 카메라 모형을 이용하여, 새로운 좌표 변환식을 유도하였다. 이 영상좌표 변환식은 참조점을 이용하지 않으며, 수면과 카메라간의 연직 거리와 카메라의 기울어진 각도만을 이용하여 좌표 변환이 가능한 방법이다. 참조점을 필요로 하지 않기 때문에 측량의 번거로움이 없으며, 변환식내에서 내삽을 하지 않기 때문에 영상 전체에 대해 고른 좌표 변환이 가능한 장점을 지니고 있다.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.205-213
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• 2012

Transforming response variable is a general tool to adapt data to a linear regression model. However, it is well known that response transformations in linear regression are very sensitive to one or a few outliers. Many methods have been suggested to develop transformations that will not be influenced by potential outliers. Recently Cheng (2005) suggested to using a trimmed likelihood estimator based on the idea of the least trimmed squares estimator(LTS). However, the method requires presetting the number of outliers and needs many computations. A new method is proposed, that can solve the problems addressed and improve the robustness of the estimates. The method uses a stepwise procedure, suggested by Hadi and Simonoff (1993), to detect outliers that determine response transformations.