• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.109-115
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• 2001

Wavelet coefficients are known to have decorrelating properties, since wavelet is orthonormal transformation. but empirically, those wavelet coefficients of images, like edges, are not statistically independent. Jansen and Bultheel(1999) developed the empirical Bayes approach to improve the classical threshold algorithm using local characterization in Markov random field. They consider the clustering of significant wavelet coefficients with uniform distribution. In this paper, we developed wavelet thresholding algorithm using Laplacian distribution which is more realistic model.

• East Asian Economic Review
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• 제28권1호
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• pp.95-140
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• 2024

This study empirically investigates the international transmission of China's uncertainty shocks. It estimates a time-varying parameter Bayesian global structural vector autoregressive model (TVP-BGVAR) using time series data for 33 countries to evaluate heterogeneous international linkage across countries and time. Uncertainty shocks are identified via sign restrictions. The empirical results reveal that an increase in uncertainty in China negatively affects the global economy, but those effects significantly vary over time. The effects of China's uncertainty shocks on the global economy have been significantly altered by China's WTO accession, the global financial crisis, and the recent US-China trade conflict. Furthermore, the effects of China's uncertainty shocks, typically on inflation, differ significantly across countries. Moreover, Trade openness appears crucial in explaining heterogeneous GDP responses across countries, whereas the international dimension of monetary policy appears to be important in explaining heterogeneous inflation responses across countries.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.33-42
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• 2020

The neoclassical economic supporters have suggested that foreign direct investment and raw material (e.g., coal, electricity, gas, and oil) are critical economic growth inputs. Few previous studies have analyzed the relationship between foreign direct investment and energy consumption on economic growth. However, existing studies usually have applied the frequentist inference. The limitation of the frequentist inference is that, if the coefficient of the independent variable is not yet significant, then conclusions might be unreliable. By applying the Bayesian approach, the main aim of this study is to revisit the impact of foreign direct investment, electricity consumption, and urbanization on economic growth in six ASEAN countries from 1980 to 2016. The obtained outcome shows that the impact of electricity consumption is evident and positive on economic growth in both frequentist and Bayesian inferences. However, the influence of foreign direct investment is not identified by frequentist inference, while Bayesian inference provides evidence that foreign direct investment is a moderately positive impact on economic growth. The empirical result from Bayesian inference contributes to the literature on foreign direct investment modeling and could be of significant importance for a more efficient foreign direct investment attracting and achieve sustainability in the long-term.

• 한국수자원학회논문집
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• 제51권9호
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• pp.813-826
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• 2018

최근 기후변동성으로 유발되는 불안정한 기상상태를 효과적으로 관측하고자 레이더가 도입되고 있다. 레이더는 경험식으로 산정된 Z-R 관계식을 통하여 레이더 강우량을 제시하게 된다. 이 과정에서 레이더 강우량은 필연적으로 지상에 도달하는 실제 강우량과는 정량적 오차가 발생하게 된다. 본 연구는 확률통계학적 방법론을 이용하여 Z-R 관계식 매개변수 산정과정에서 우리나라의 강우특성을 고려함과 동시에 Z-R 관계식 매개변수의 불확실성을 정량적으로 제시하고자 한다. 강우의 계절성을 고려하여 Z-R 관계식 매개변수를 추정하는 과정에서 Bayesian 추론기법을 도입하여 생산된 레이더 강우량은 기존의 Z-R 관계식에 비하여 개선된 통계적 효율기준을 제시하였다. 따라서 Bayesian 추론기법을 활용한 Z-R 관계식 매개변수 산정은 정량적으로 신뢰성 있는 고해상도 강우정보의 생산은 고도화된 수문해석 및 기상예보 지원을 가능케 할 것으로 판단된다.

• 응용통계연구
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• 제22권6호
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• pp.1167-1176
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• 2009

항만이나 공항의 소유구조에 대한 효율성 분석은 지금까지 서로 엇갈리는 결과를 제시하고 있다. 즉, 민영화 또는 공영화로 인한 효율성 효과가 자료 또는 분석 방법에 따라서 일치된 결과를 보여주지 않고 있다. 본 논문은 국내의 항만이 포함된 국제 항만 교역데이터베이스를 기반으로 베이지안 확률적 프런티어 모형을 적용하여 항만의 소유 구조에 따른 효율성 분석을 하였다. 소유 구조는 Tongzon과 Heng (2005)의 방법을 따랐으며 제안된 몇 가지 모형과 그들의 모형을 DIC 통계량을 이용하여 비교하였다. 베이지안 추론에 필요한 MCMC 방법은 Griffin과 Steel (2007)에서 소개된 WinBUGS 프로그램을 이용하여 구현하였다.

• Journal of applied mathematics & informatics
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• 제3권1호
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• pp.55-64
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• 1996

Let $X_1, ....$X_P be p($\geq$2) independent random variables, where each X1 has a gamma distribution with $k_i and ${\heta}_i$. The problem is to simultaneously estimate p gammar parameters ${\heta}_i$ under entropy loss where the parameters are believed priori. Hierarchical bayes(HB) and empirical bayes(EB) estimators are investigated. Next computer simulation is studied to compute the risk percentage improvement of the HB, EB and the estimator of Dey et al.(1987) compared to MVUE of ${\heta}$.

• 지능정보연구
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• 제3권2호
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• pp.83-91
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• 1997

DELVAUX is an inductive learning environment that learns Bayesian classification rules from a set o examples. In DELVAUX, a genetic a, pp.oach is employed to learn the best rule-set, in which a population consists of rule-sets and rule-sets generate offspring by exchanging some of their rules. We have explored a meta-learning a, pp.oach in the DELVAUX learning environment to improve the classification performance of the DELVAUX system. The meta-learning a, pp.oach learns the bias of a classifier so that it can evaluate the prediction made by the classifier for a given example and thereby improve the overall performance of a classifier system. The paper discusses the meta-learning a, pp.oach in details and presents some empirical results that show the improvement we can achieve with the meta-learning a, pp.oach.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.

• 대한산업공학회지
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• 제25권1호
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• pp.67-74
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• 1999

Market share is one of the most important measures in the valuation of prospering firm. It plays a role of composite indicator for the competitiveness of firm. So, the understanding of the underlying process of market share is inevitable factor for the econometricians and the business engager. Lately, the Korean Economy has been placed in the control of IMF. This shock will cause a lot of influence over the domestic economy. The idea that the information about the past shock-response experience will do us good for dealing with this kind of economic shocks is not new. Among numerous markets, we pay attention to the durable goods market, especially automobile market. The automobile market has large repercussion effect over the domestic economy on the issue of both national employment and technology integration. We divided the Korean automobile market into three segments: small, medium, and large-sized car, while each proportion of these segments has been changing slowly. We propose a Bayesian approach to detect and forecast structural changes in time series of the market shares in the domestic automobile market, especially for level shifts and drift changes, and compare the empirical results with other existing approaches.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.363-378
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• 2015

Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.