• 재무관리연구
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• 제26권3호
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• pp.199-226
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• 2009

본 논문은 우리나라 주식시장과 외환시장의 기대 수익률과 조건부 변동성간의 시계열적 관계를 2요인 자본자산가격결정모형(two-factor ICAPM)을 이용하여 실증 분석하였다. 주가와 환율의 조건부 분산은 GARCH 모형과 비대칭성을 반영한 GJR(1993) 모형으로 추정하였으며, 주가와 환율과의 조건부 공분산은 Bollerslev(1990)의 일정 상관관계(CCC) 모형과 Engle(2002)의 동태적 조건부상관관계(DCC) 모형을 이용하여 추정하였다. 실증 분석모형은 MGARCH-M 모형을 사용하였으며, 추정방법은 준최우추정법(QMLE)을 사용하였다. 실증 분석결과 외환위기 이후에 주식시장의 기대 수익률은 주가의 분산에 대해, 그리고 환율과의 공분산에 대해 유의한 음(-)의 관계를 갖는 것으로 나타났다. 그러나 외환시장에서 기대 수익률은 조건부 분산과 조건부 공분산에 대해 유의하지 않은 것으로 나타났다. 조건부 분산의 추정에서는 GJR 모형이 GARCH 모형에 비해 더 적합한 것으로 나타났다. 그리고 DCC 모형이 CCC 모형에 비해 설명력이 더 높은 것으로 나타났다. 본 논문의 분석결과는 주식시장에서 환율 변동이 위험 요인으로 작용하고 있기 때문에 포트폴리오 구성이나 위험 관리 등에서 환율 변동을 고려할 필요가 있고, 변수들간의 상관관계는 시변하는 모형을 사용할 필요가 있음을 시사한다.

• 한국산림과학회지
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• 제104권1호
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• pp.111-116
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• 2015

본 연구의 목적은 임의효과(random effect)를 포함하는 혼합모형(mixed model)을 이용하여 흉고직경과 수고의 변화량을 평가하는데 있다. 강원도 굴참나무 임분을 대상으로 흉고직경과 수고를 조사하고 3년 후 동일 임분을 재조사하였다. 혼합모형에서 굴참나무의 흉고직경-수고 관계는 고정효과(fixed effect)이고 초기측정과 반복측정의 흉고직경과 수고 차이를 임의효과로 설정하였다. 임의효과에 따른 모형의 적합도를 검정하기 위하여 아카이케의 정보기준(akaike information criterion, AIC)을 참고하고 반복 측정에 따른 분산-공분산 행렬과 오차항을 산정하였다. 추정된 공분산은 -0.0291이고 오차항은 0.1007을 나타내었다. 분산-공분산 행렬을 이용한 임의효과가 포함된 모형의 AIC(=-215.5)는 고정효과를 고려한 모형의 AIC(=-154.4)에 비해 낮은 수치를 나타내었다. 이러한 결과는 범주형 자료의 임의효과가 모형 개발에 반영되는 결과인 것으로 조사되었다. 그러므로, 본 연구에서 적용된 혼합모형은 반복 측정 자료를 이용한 모형 개발에 활용이 가능한 것으로 판단된다.

• 품질경영학회지
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• 제25권2호
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• pp.102-111
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• 1997

In this paper I discuss a method of constructing the confidence region for the logistic response surface model. The construction involves a, pp.ication of a general fitting procedure because the log odds is linear in its parameters. Estimation of parameters of the logistic response surface model can be accomplished by maximum likelihood, although this requires iterative computational method. Using the asymptotic results, asymptotic covariance of the estimators can be obtained. This can be used in the construction of confidence regions for the parameters and for the logistic response surface model.

• 한국전자파학회논문지
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• 제21권1호
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• pp.20-27
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• 2010

본 논문은 space-time signal processing(STAP)의 신호 모델과 불균일한 클러터 환경을 제시하고 이를 극복하고자 연구된 nonhomogeneity detector(NHD)의 사용 이후에도 일어나는 심각한 성능 저하를 극복하고자 중위수(median)를 이용한 간섭 공분산 행렬의 새로운 예측 방법을 제시하였다. 또한 대각 로드(diagonal loading)를 적용하여 고유값(eigen value) 특성을 개선시켰으며 signal to interference plus noise ratio(SINR) 손실을 계산하여 비교하였다. 마지막으로 modified sample matrix inversion(MSMI) 통계량으로 목표물 검출 능력을 비교한 결과 제시된 방법이 평균값(average)으로 정의된 기존의 방법보다 우수한 성능을 보임을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권9호
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• pp.3146-3158
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• 2014

Efficient depth map coding is very crucial to the multi-view plus depth (MVD) format of 3-D video representation, as the quality of the synthesized virtual views highly depends on the accuracy of the depth map. Depth map contains smooth area within an object but distinct boundary, and these boundary areas affect the visual quality of synthesized views significantly. In this paper, we characterize the depth map by an auto-covariance analysis to show the locally anisotropic features of depth map. According to the characterization analysis, we propose an efficient depth map coding scheme, in which the directional discrete cosine transforms (DDCT) is adopted to substitute the conventional 2-D DCT to preserve the boundary information and thereby increase the quality of synthesized view. Experimental results show that the proposed scheme achieves better performance than that of conventional DCT with respect to the bitrate savings and rendering quality.

• 전기학회논문지
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• 제68권1호
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• pp.108-121
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• 2019

This paper presents the study results on the design of the correction filter to improve the azimuth error estimation of the high-speed guided missile launched from the warship after the transfer alignment. We theoretically proved that the transfer alignment performance is determined by the accuracy of the marine inertial navigation system and the observability of the attitude error state variable in the transfer alignment filter, and that most of navigation errors in high-speed guided missile are caused by azimuth error. In order to improve the azimuth estimation performance of the correction filter, the multiple adaptive estimation method and the adaptive filters adapting the measurement noise covariance or the process noise covariance are proposed. The azimuth estimation performance of the proposed adaptive filter and the existing Kalman filter are compared and analyzed each other for 8 different transfer alignment accuracy cases. As a result of comparison and analysis, it was confirmed that the adaptive filter adapting the process noise covariance has the best azimuth estimation performance. These results can be applied to the design of correction filters for high-speed guided missile.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.597-598
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• 2015

In order to improve the reliability of cost estimation results using CBR, there has been a continuous issue on similarity measurement to accurately compute the distance among attributes and cases to retrieve the most similar singular or plural cases. However, these existing similarity measures have limitations in taking the covariance among attributes into consideration and reflecting the effects of covariance in computation of distances among attributes. To deal with this challenging issue, this research examines the weighted Mahalanobis distance based similarity measure applied to CBR cost estimation and carries out the comparative study on the existing distance measurement methods of CBR. To validate the suggest CBR cost model, leave-one-out cross validation (LOOCV) using two different sets of simulation data are carried out. Consequently, this research is expected to provide an analysis of covariance effects in similarity measurement and a basis for further research on the fundamentals of case retrieval.

• 한국물환경학회지
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• 제26권2호
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• pp.252-260
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• 2010

The point rainfall measurements need to be converted to the areal rainfall by means of mean areal precipitation (MAP) estimation methods. And it is not appropriate to evaluate the areal rainfall with constant drift because of the geomorphological influences to rainfall field. Non-stationarity should be applied to the estimation of the areal rainfall, therefore, to consider these effects. Kriging methods with special functional would be a suitable tool in this case. Generalized covariance Kriging method is the most developed one among different Kriging methods. From this point of view this study performs the analysis of its applicability to distributed runoff model. For these purpose, distributed rainfall was created by Thiessen and Kriging method. And distributed rainfall of each method was applied into HyGIS-GRM. The result of applying, Runoff was different in the rainfall data form. Therefore, To apply Kriging method with physical meaning is that it is the useful method as distributed rainfall-runoff model.

• 한국군사과학기술학회지
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• 제21권3호
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• pp.403-412
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• 2018

In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.