• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.105-106
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• 2018

본 논문에서는 동적 프로젝션 맵핑을 구현하기 위하여 3차원 공간의 깊이 정보와 대상 객체의 색상영상에서의 특징점을 추출하여 3차원 공간상에서 움직이는 2차원 평면 객체의 자세를 안정적으로 추정하는 기법을 제안한다. 제안 기법은 타겟 이미지를 출력하여 타겟 이미지 보다 큰 평면 패널에 부착하고, 이 평면 패널을 3차원 공간상에서 움직이는 환경에서 타겟 이미지의 자세를 안정적으로 추정하기 위하여 고안되었다. 제안 기법에서는 우선 패널이 움직일 수 있는 깊이 영역을 지정하여 해당 깊이 영역에 존재하는 2차원 패널을 추출하고, 패널의 사각영역을 추출한다. 또한, 색상 영상에 SURF 알고리즘을 적용하여 2차원 평면상에 부착된 타겟 이미지의 영역을 색상 특징을 기반으로 함께 추출하여 패널의 사각 영역과 타겟 이미지의 상대적인 위치 정보를 추출한다. 셋업 단계에서 추출된 타겟 이미지의 상대적인 위치 정보를 이용하여, 조명의 변화에 의하여 순간적으로 타겟 이미지의 특징점 추적에 실패한 경우, 패널의 사각 영역에 의해 계산된 타겟 이미지의 상대적 위치 정보를 계산하여 자세 추정에 사용함으로써 움직이는 타겟 이미지의 3차원 자세를 안정적으로 추정할 수 있도록 하였다.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.55-70
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• 2000

본 논문에서는 내포오차성분을 가지는 패널회귀모형에서 회귀계수에 대하여 다양한 추정량들을 유도하고, 추정량들의 효율성을 모의실험을 통하여 평균제곱오차의 기준에서 비교하였다. 모의실험 결과, 제안된 FGLS 추정량들은 GLS추정량과 효율성에서 서로 큰 차이를 보이지 않았으며, 계산상 더욱 복잡한 ML, REML 추정량 및 MIVQUE와 거의 비슷한 효율성을 보여주었다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1199-1210
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• 2013

The high unemployment rate is one of the major problems in most countries nowadays. Hence, the demand for small area labor statistics has rapidly increased over the past few years. However, since sample surveys for producing official statistics are mainly designed for large areas, it is difficult to produce reliable statistics at the small area level due to small sample sizes. Most of existing studies about the small area estimation are related with the estimation of parameters based on cross-sectional data. By the way, since many official statistics are repeatedly collected at a regular interval of time, for instance, monthly, quarterly, or yearly, we need an alternative model which can handle this type of panel data. In this paper, we derive the generalized kernel estimating equation which can model time-dependency among response variables and handle repeated measurement or panel data. We compare the proposed estimating equation with the generalized linear model and the generalized estimating equation through simulation, and apply it to estimating the unemployment rates of 25 areas in Gyeongsangnam-do and Ulsan for 2005.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.94-101
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• 1994

본 논문은 패널(panel) 자기회귀 모형에서 자기회귀 계수의 추정을 베이지안 방법으로 접근하였는데, 이 때 특별히 Gibbs Sampling 방법을 이용하여 사후분포를 계산하였다. 또한 모의 실험을 통하여 자기회귀계수를 Gibbs Sampling 방법으로 추정한 베이지안 추정치가 non-Bayesian 방법으로 구한 추정치보다 더 우월함을 보였다.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.367-374
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• 1997

In panel surveys it is necessary to manage both sampling frame and sample units across time. When sample is updated according to the change of its frame, it should be incorporated in the estimation procedure. This paper derives the bias of the conventional estimator caused by neglecting the change of sample, and provides a bias-adjusted estimator with its variance.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.103-111
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• 2011

To evaluate highway safety countermeasures or identify high risk sites, the expected crashes for a site (or segment) have been estimated using the panel crash data. Past studies show that two different methods can be employed to estimate the expected crashes: observed crash based method and empirical Bayes (EB) method. This study conducts a simulation study to analyze how the estimation errors of the two estimates are affected by the different structures of the panel crash data and the presence of the change in safety over time. The results disclose that the estimation errors of the observed crash based estimates (i.e. the mean observed crash and comparative parallel estimate) are always greater than those of the EB estimates regardless of the structure of the panel crash data and the presence of the change in safety over time. Thus, it is highly recommended that the EB method be used in the study of traffic safety to obtain more reliable estimates for the expected crashes. In addition, this study corroborates that the estimation errors of the two estimates decrease as the analysis periods increase if safety does not change over time. Hence, it is also recommended that the 1-year analysis period used for identifying high risk sites in Korea be extended to produce more efficient estimates of the time-constant expected crashes.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.521-534
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• 2006

This paper considers a panel regression model with ill-posed data and proposes the generalized maximum entropy(GME) estimator of the unknown parameters. These are natural extensions from the biometries, statistics and econometrics literature. The performance of this estimator is investigated by using of Monte Carlo experiments. The results indicate that the GME method performs the best in estimating the unknown parameters.

• Journal of Energy Engineering
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• v.26 no.2
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• pp.80-92
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• 2017

This paper attempts to estimate the diesel fuel demand function in Korea using panel data panel data of 16 major cities or provinces which consist of diesel demands, diesel market prices and gross value added from the year 1998 to 2015. I apply panel GLS(generalized least square) model, fixed effect model, random effect model and dynamic panel model to estimating the parameters of the diesel fuel demand function. The results show that short-run price elasticities of the diesel fuel demand are estimated to be -0.2146(panel GLS), -0.2886(fixed effect), -0.2854(random effect), -0.1905(dynamic panel) respectively. And short-run income elasticities of the diesel fuel demand are estimated to be 0.7379(panel GLS), 0.4119(fixed effect), 0.7260(random effect), 0.4166(dynamic panel) respectively. The short-run price and income elasticities explain that demand for diesel fuel is price- and income-inelastic. The long-run price and income elasticities are estimated to be -0.4784, 1.0461 by dynamic panel model, which means that demand for diesel fuel is price-inelastic but income-elastic in the long run. In addition I apply dummy variable model to estimate the effect of 16 major cities or provinces on diesel demands. The results show that diesel demands is affected 10 regions on the basis of Seoul.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.25-34
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• 2011

The transition probability can be used for the estimation of subpopulation total in panel data analysis. In this paper a real data analysis is performed and the sensitivity of the sample size allocated in the subpopulation is examined by small simulation studies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.424-436
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• 1993

패널내 추계적 성분들의 공분산 관계(variance-covariance structure)를 이용한 ML 추정법을 항상소득가설(PIH)의 검증에 적용하였다. Hall & Mishkin의 모형을 기초로 분기별 이분산성(heteroscedasticity)을 고려한 모형의 추정결과 전체 소비변동 중 약 11%가 과도민감성에 의한 것으로 나타났다.