• Journal of Korea Port Economic Association
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• v.26 no.2
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• pp.82-98
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• 2010

The purpose of this paper is to suggest the efficiency measurement way of Korean seaport by using Average Index Transformation model of fuzzy DEA(Data Envelopment Analysis). Two inputs[cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, and the number of ship calls] are used in 1995 and 2004 for 26 Korean seaports. Empirical main results are as follows: First, Tongyung, Gohyun, Okpo, and Sogcho Ports are efficient, and Yeasu Port shows the high efficiency level over 95% under input oriented CCR model. Gohyun and Sogcho Ports showed the most efficient score under average index transformation model. Okpo and Yeasu Ports increased their efficiency scores as the lamda(λ) values are up. The empirical results of fuzzy DEA average index transformation model for Wando, Yeasu, and Seoguipo ports showed that if the lamda values are higher, the efficiency scores are also higher. The main policy implication based on the findings of this study is that the management manager of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the fuzzy DEA average index transformation model for deciding the size of inputs including the port investment amount and evaluating the port efficiency.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.541-550
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• 2007

One of main aspects of time series analysis is to forecast future values of series based on values up to a given time. The prediction interval for future values is usually obtained under the normality assumption. When the assumption is seriously violated, a transformation of data may permit the valid use of the normal theory. We investigate the prediction problem for future values in the original scale when transformations are applied in ARMA models. In this paper, we introduce the methodology based on Yeo-Johnson transformation to solve the problem of skewed data whose modelling is relatively difficult in the analysis of time series. Simulation studies show that the coverage probabilities of proposed intervals are closer to the nominal level than those of usual intervals.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.67-71
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• 2004

Increasing number and acquisition rate of satellite imagery promoted researches related with DEM generation based on satellite imagery. SPOT image gave us advantage to generate DEM which covers wide area of $60km{\times}60km$. In the case of rigorous sensor model of SPOT imagery, ephemeris data and several ground control points are need and requires arduous computational costs to produce DEM. In this study, using alternative sensor model based on Direct Linear Transform, we generated DEM using small number of ground control points. As a result, it was possible to acquire the DEM with suitable accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.213-213
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• 2017

저수지 유입량은 효율적 저수지 운영을 위해 중요한 요소로, 이는 하류 하천 등과 복합적으로 연계되기에 통합적 수자원 관리를 위해서 정확한 추정이 중요하다. 국내의 일부 저수지에서는 상류에서 유입되는 유량을 측정하고 있으나, 모든 저수지에 대해 측정하기에는 현실적 한계가 있다. 한편, 한국농어촌공사에서는 유효저수량 10만톤 이상 저수지에 대해 수위 계측기를 설치하여 수위자료를 관측하고 있으며, 이는 수위-내용적 곡선을 통해 저수량으로 변환이 가능하다. 저수량 자료가 확보되면 물수지식 기반으로 간접적으로 유입량의 추정이 가능하나, 수위가 상승하는 구간에 대해서만 적용이 가능하기에 연속적인 자료의 확보에 한계가 있다. 이 경우 불연속 유량자료를 대상으로 수문모형의 매개변수를 최적화하여 장기간 연속자료로 변환하는 것이 한 방안이 될 수 있다. 본 연구에서는 저수지 수위 기반으로 추정된 간헐적 유입량 자료를 기반으로 수문모형의 매개 변수를 최적화하여 장기유량으로 변환하고자 한다. 수문 모형과 매개변수 최적화 기법은 각각 Tank 모형과 SCE (Shuffled Complex Evolution) 기법을 이용하였다. 매개변수 최적화를 위한 목적함수는 고유량 저유량 총량 분산 관련 지표에 가중치를 부여한 다중 목적함수로 설정하였으며, 이를 통해 도출된 다양한 매개변수 후보군 중 고유량 저유량 총량 유황곡선의 유사정도가 전반적으로 일치하는 매개변수 군을 선택하였다. 본 연구 결과는 미계측 저수지 유입량을 추정할 수 있음으로써 저수지의 효율적인 물관리와 용수관리 의사결정에 활용할 수 있을 것으로 사료된다.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.21-29
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• 2009

Engle and Russell (1998) proposed the ACD(Autoregressive Conditional Duration) model to explain the relationship between the prices and the duration times of the stocks. In this paper, we first introduce the various types of the ACD models such as the linear ACD, log ACD and Box-Cox ACD models and we evaluate the performance of the models for analysing the transaction data of the stocks in Korea.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.57-71
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• 2002

We introduce three types of exponential survival models, such as simple model, change-point model and finite mixture model in this paper. Among these models, in order to choose the best model, the model choice method is proposed using Gelfand and Ghosh(1998)'s idea. Then to avoid the computational difficulties, data augmentation method (Tanner and Wong, 1987) and Gibbs sampler (Gelfand and Smith, 1990) are employed. Our methodology is applied to both simulated data and Stangl (1991)'s On-impramint Hydrochloride data.

• Journal of the Korean Statistical Society
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• v.8 no.2
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• pp.109-116
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• 1979

두 개의 변수의 대체효과(substitution effect)를 연구하기 위하여 수요 또는 공급의 모형을 만들었을 경우 이에 관련된 변수들의 이름이 중요시 된다. 실제 관측 자료를 사용하였을 경우 흔히 일어나는 다공선성(multicollinearity) 문제를 다루기 위한 대안으로써 선형회귀선을 예로 들어 능형회귀기법(ridge regression technique)과 요인분석기법(factor analytic technique)을 소개하였으며 이에서 얻어지는 계수(coefficient)를 OLS 추정치로 설명하기 위하여 원래의 자료를 변환하였다. 실지 수요와 공급의 모형이 비선형일 경우 일반적으로 능형회귀나 요인분석을 쓰지 못한다는 점을 감안, 이러한 방법을 자료의 변환방법으로 설명함으로써 비선형모형에서도 다공선성문제를 위하여 능형회귀분석법이나 요인분석기법을 사용할 수 있도록 하였다.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.155-160
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• 2014

When we collect marketing data, we can only obtain the bimonthly or quarterly data but the monthly data be available. If we evaluate or predict monthly market condition or establish monthly marketing strategies, we need to disaggregate these bimonthly or quarterly data to the monthly data. In this paper, for bimonthly or quarterly data, we introduce some methods of disaggregation to monthly data. These disaggregation methods include the simple average method, the growth rate method, the weighting method by the judgment of experts, and variable decomposition method using 12 month moving cumulative sum. In this paper, we applied variable decomposition method to disaggregate for bimonthly data of sum of electronics sales in a European country. We, also, introduce how to use this method to predict the future data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.231-240
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• 2010

If only fixed effects exist in a 4 $\times$ 4 balanced incomplete block design, powers of FR statistic for testing a main effect show the highest level with a few replications. Under the exponential and double exponential distributions, FR statistic shows relatively high powers with big differences as compared with the F statistic. Further in a traditional balanced incomplete block design, powers of FR statistic having a fixed main effect and a random block effect show superior preference for all situations without regard to the effect size of a main effect, the parameter size and the type of population distributions of a block effect. Powers of FR statistic increase in a high speed as replications increase. Overall power preference of FR statistic for testing a main effect is caused by unique characteristic of a balanced incomplete block design having one main and block effect with missing observations, which sensitively responds to small increase of main effect and sample size.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.683-691
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• 2012

In $4{\times}4$ graeco-latin square design, powers of rank transformed statistic for testing the main effect are superior to powers of parametric statistic without regard to the effect structure with equally or unequally spaced effect levels as well as the type of population distributions such as exponential, double exponential, normal and uniform distribution. As numbers of block effect or effect sizes are decreased, powers of rank transformed statistic are much higher than powers of parametric statistic. In case that block effects are smaller than a main effect or one block effect is higher than other block effects, powers of rank transformed statistic are much higher than powers of parametric statistic in $4{\times}4$ graeco-latin square design with three block effects and one main effect.