• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.1-29
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• 2007

Suppose one is trying to estimate a high dimensional vector of parameters from a series of one observation per parameter. Often, it is possible to take advantage of sparsity in the parameters by thresholding the data in an appropriate way. A marginal maximum likelihood approach, within a suitable Bayesian structure, has excellent properties. For very sparse signals, the procedure chooses a large threshold and takes advantage of the sparsity, while for signals where there are many non-zero values, the method does not perform excessive smoothing. The scope of the method is reviewed and demonstrated, and various theoretical, practical and computational issues are discussed, in particularly exploring the wide potential and applicability of the general approach, and the way it can be used within more complex thresholding problems such as curve estimation using wavelets.

• 대한지리학회지
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• 제51권3호
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• pp.367-380
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• 2016

본 연구에서는 우리나라에서 발생한 저체중아 출생 집계 자료를 공간적으로 지도화하기 위한 기법들을 검토 비교하고, 이를 기반으로 우리나라의 LBW 지도를 작성하였다. 표준화사망률이나 조사망률 등은 역학 분야에서 지속적으로 광범위하게 사용되고 있는 지표이다. 그러나 이러한 표준화사망률은 집계 단위의 샘플 수에 영향을 많이 받는다는 단점을 가지고 있다. 이에, 본 연구에서는 베이지언 기법을 활용하여 샘플 수에 따른 통계적 변동성을 감소시키고자 하였다. 이를 위해 경험적 베이지언 기법과 풀 베이지언 기법을 모두 활용하였고, 결과적으로 유사한 통계량을 산출한 것을 확인할 수 있었다. 반면, SMR 기반의 통계량은 높은 분산을 가지고 있음을 확인하였다. 연구의 결과에 따른 통계 지도는 우리나라 저체중아 출생의 높은 위험도를 가지는 지역들을 파악할 수 있도록 한다.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.37-47
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• 2022

This study uses monthly data from January 2009 to December 2020 to examine the effectiveness of foreign currency intervention and its influence on monetary policy in Vietnam using a Hierarchical Bayesian VAR model. The findings suggest that foreign exchange intervention has little influence on the exchange rate level or exports, but it can significantly minimize exchange rate volatility. As a result, we can demonstrate that the claim that Vietnam is a currency manipulator is false. As well, the forecast error variance decomposition results reveal that interest rate differentials mainly determine the exchange rate level instead of foreign exchange intervention. Moreover, the findings suggest that foreign exchange intervention is not effectively sterilized in Vietnam. Inflation is caused by an increase in international reserves, which leads to an expansion of the money supply and a decrease in interest rates. Although the impact of foreign exchange intervention grows in tandem with the growth of international reserves, if the sterilizing capacity does not improve, rising foreign exchange intervention will instead result in inflation. Finally, we use a rolling window approach to examine the time-varying effect of foreign exchange intervention.

• Asia Marketing Journal
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• 제22권1호
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• pp.41-60
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• 2020

The goal of the study is to understand the role of social norm in purchase decisions where demand is revealed in the form of multiple-discreteness. Consumers are socially engaged in various activities through the expectation from others in their community. Actions or decisions are likely to reflect this influence. This implicit or explicit social norm is revealed as the rules, regulations, and standards that are understood, shared, endorsed, and expected by group members. When consumers' decisions are in distance from the norm, they come to face discomfort such as shame, guilt, embarrassment, and anxiety. These pressure act as a constraint as opposed to utility in their decision making. In this study, the effect of social norms on consumer demand is captured via multiple constraint model where constraints are not only from budget equation but also from psychological burden induced by the deviation from the norm. The posterior distributions of model parameters were estimated via conjoint study allowing for heterogeneity via hierarchical Bayesian framework. Individual characteristics such as age, gender and work experience are also used as covariates for capturing the observed heterogeneity. The empirical results show the role of social norm as constraint in consumers' utility maximization. The proposed model accounting for social constraint outperforms the standard budget constraint-only model in terms of model fit. It is found that people with longer job experience tend to be more robust and resistant to the deviation from the norm. Incorporating social norm into the utility model allows for another means to disentangle the reason for no-purchase as 'not preferred' and 'not able to buy'.

• 한국지형학회지
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• 제26권3호
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.181-193
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• 2022

This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

• 한국정보처리학회논문지
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• 제6권7호
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• pp.1841-1848
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• 1999

델보는 주어진 사례의 집합으로부터 이들 사례들을 분류할 수 있는 베이지안 분류 규칙들로 이루어진 규칙 집합을 습득하는 유전학 기반 귀납적 학습 시스템이다. 규칙 집합의 습득과정에서 델보가 당면하게 되는 한 가지 문제점은 학습 과정이 최적의 규칙 집합이 아닌 지역 최적치를 습득하고 종료하는 경우가 가끔 발생한다는 것이다. 다른 하나의 문제점은 훈련 사례에 대한 경우와는 달리 새로운 평가 사례에 대해 분류 성능이 현저히 저하되는 규칙 집합을 습득하는 경우가 가끔 발생한다는 것이다. 본 논문에서는 이러한 문제점을 해결하여 보다 성능이 향상된 분류 시스템을 구축하기 위한 기법으로 엔-버전 시스템을 구축함으로써 분류 시스템의 전체적인 성능을 향상시키는 기법이다. 엔-버전 학습법의 구현을 위해 다수의 규칙 집합을 이용하여 최종 분류 결과를 도출해 내기 위한 기법과 습득된 규칙 합들로부터 분류 시스템을 구축하기 위한 최적의 규칙 집합의 조합을 찾기 위한 기법을 제시하고 다수의 사례 집합을 이용하여 엔-버전 학습법이 델보의 학습 환경에 미치는 영향을 평가하였다.

• 한국항해항만학회지
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• 제33권1호
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• pp.9-19
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• 2009

본 논문에서는 상선의 운항 사고에 관한 양적 위기평가에 관한 실험적인 접근방법들을 기술했다. 이 연구의 목적은 국제해사기구의 공식 안전성 평가(FSA)를 기반으로 운항 사고에 크게 기여하는 요소들을 분석하고, 양적 위기평가기법에 기반을 둔 운항 사고의 확률적인 위기수준을 평가한 후, 선박 안전을 저해할 수 있는 운항 사고 위기를 예측하는 것이다. 확률지수(PI)와 심각성지수(SI) 구성된 위기지수(RI)에 대한 운항 사고의 확률적인 위기수준은 베이지안 이론을 적용한 베이지안 네트워크를 기반으로 본 연구에서 제안한 운항사고 위기 모델을 이용해서 예측했다. 그리고 355건의 핵심 손상 사고기록으로 구성된 시나리오 그룹을 이용하여 제안한 모델의 적용 가능성을 평가하였다. 평가결과, 예측한 PI의 정답률 $r_{Acc}$은 82.8%로 나타났고, $S_p{\gg}1.0$과 $S_p{\ll}1.0$에 포함되는 PI 변수들의 민감도 초과비율은 10% 이내로 나타났으며, 예측한 SI의 평균 오차 $\bar{d_{SI}}$는 0.0195로 나타났고, 예측한 RI의 정답률은 91.8%로 나타났다. 이러한 결과는 제안한 모델과 방법이 실제 해상운송 현장에 적용 가능함을 나타낸다.

• Steel and Composite Structures
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• 제44권1호
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• pp.119-139
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• 2022

This paper aims to use the artificial intelligence approach to develop a new model for predicting the ultimate axial strength of the circular concrete-filled steel tubular (CFST) stub columns. For this, the results of 314 experimentally tested circular CFST stub columns were employed in the generation of the design model. Since the influence of the column diameter, steel tube thickness, concrete compressive strength, steel tube yield strength, and column length on the ultimate axial strengths of columns were investigated in these experimental studies, here, in the development of the design model, these variables were taken into account as input parameters. The model was developed using the backpropagation algorithm named Bayesian Regularization. The accuracy, reliability, and consistency of the developed model were evaluated statistically, and also the design formulae given in the codes (EC4, ACI, AS, AIJ, and AISC) and the previous empirical formulations proposed by other researchers were used for the validation and comparison purposes. Based on this evaluation, it can be expressed that the developed design model has a strong and reliable prediction performance with a considerably high coefficient of determination (R-squared) value of 0.9994 and a low average percent error of 4.61. Besides, the sensitivity of the developed model was also monitored in terms of dimensional properties of columns and mechanical characteristics of materials. As a consequence, it can be stated that for the design of the ultimate axial capacity of the circular CFST stub columns, a novel artificial intelligence-based design model with a good and robust prediction performance was proposed herein.

• Computers and Concrete
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• 제24권6호
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• pp.541-553
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• 2019

Alkali-silica reaction (ASR) in concrete can induce degradation in its mechanical properties, leading to compromised serviceability and even loss in load capacity of concrete structures. Compared to other properties, ASR often affects the modulus of elasticity more significantly. Several empirical models have thus been established to estimate elastic modulus reduction based on the ASR expansion only for condition assessment and capacity evaluation of the distressed structures. However, it has been observed from experimental studies in the literature that for any given level of ASR expansion, there are significant variations on the measured modulus of elasticity. In fact, many other factors, such as cement content, reactive aggregate type, exposure condition, additional alkali and concrete strength, have been commonly known in contribution to changes of concrete elastic modulus due to ASR. In this study, an artificial intelligent model using artificial neural network (ANN) is proposed for the first time to provide an innovative approach for evaluation of the elastic modulus of ASR-affected concrete, which is able to take into account contribution of several influence factors. By intelligently fusing multiple information, the proposed ANN model can provide an accurate estimation of the modulus of elasticity, which shows a significant improvement from empirical based models used in current practice. The results also indicate that expansion due to ASR is not the only factor contributing to the stiffness change, and various factors have to be included during the evaluation.