• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.405-414
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• 2002

We consider the problem of estimating the error variance of in a two-way mixed-effects ANOVA model using noninformative priors. First, we derive Jeffreys' prior, a reference prior, and matching priors. We then provide marginal posterior distributions under those noninformative priors. Finally, we provide graphs of marginal posterior densities of the error variance and credible intervals for the error variance in two real data set and compare these credible intervals.

• The Korean Journal of Applied Statistics
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• v.2 no.2
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• pp.27-35
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• 1989

This article deals with statistical inference on Interleukin-2 titer of which the clinical applications to cancer immunotherapy and some immunodeficiency diseases have been widely tried. A Linear model and the Bayesian approach are used to explain the bioassay which performs the measurements of IL-2 activity from an patient and an inference procedure including confidence intervals for the IL-2 titer of the patient through comparision with the Standard IL-2 is suggested and a real case of example is illustrated.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.955-968
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• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.791-803
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• 2016

Recently, frequency of extreme rainfall events in South Korea has been substantially increased due to the enhanced climate variability. Korea is prone to flooding due to being surrounded by mountains, along with high rainfall intensity during a short period. In the past three decades, an increase in the frequency of heavy rainfall events has been observed due to enhanced climate variability and climate change. This study aimed to analyze extreme rainfalls informed by their frequency of occurrences using a long-term rainfall data. In this respect, we developed a Poisson-Generalized Pareto Distribution (Poisson-GPD) based rainfall frequency method which allows us to simultaneously explore changes in the amount and exceedance probability of the extreme rainfall events defined by different thresholds. Additionally, this study utilized a Bayesian approach to better estimate both parameters and their uncertainties. We also investigated the synoptic patterns associated with the extreme events considered in this study. The results showed that the Poisson-GPD based design rainfalls were rather larger than those of based on the Gumbel distribution. It seems that the Poisson-GPD model offers a more reasonable explanation in the context of flood safety issue, by explicitly considering the changes in the frequency. Also, this study confirmed that low and high pressure system in the East China Sea and the central North Pacific, respectively, plays crucial roles in the development of the extreme rainfall in South Korea.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.331-344
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• 2016

Whole Crop Barley (WCB) is a representative self-sufficient winter annual forage crop, along with Italian Ryegrass (IRG), in Korea. In this study, we examined the path relationship between WCB yield and climate factors such as temperature, precipitation, and sunshine duration using a structural equation model. A Bayesian approach was considered to overcome the limitations of the small WCB sample size. As prior distribution of parameters in Bayesian method, standard normal distribution, the posterior result of structural equation model for WCB, and the posterior result of structural equation model for IRG (which is the most popular winter crop) were used. Also, Heywood case correction in prior distribution was considered to obtain the posterior distribution of parameters; in addition, the best prior to fit the characteristics of winter crops was identified. In our analysis, we found that the best prior was set by using the results of a structural equation model to IRG with Heywood case correction. This result can provide an alternative for research on forage crops that have hard to collect sample data.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.523-534
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• 2021

Meteorological drought originates from a precipitation deficiency and propagates to agricultural and hydrological droughts through the hydrological cycle. Comparing with the meteorological drought, agricultural and hydrological droughts have more direct impacts on human society. Thus, understanding how meteorological drought evolves to agricultural and hydrological droughts is necessary for efficient drought preparedness and response. In this study, meteorological and hydrological droughts were defined based on the observed precipitation and the synthesized streamflow by the land surface model. The Bayesian network model was applied for probabilistic analysis of the propagation relationship between meteorological and hydrological droughts. The copula function was used to estimate the joint probability in the Bayesian network. The results indicated that the propagation probabilities from the moderate and extreme meteorological droughts were ranged from 0.41 to 0.63 and from 0.83 to 0.98, respectively. In addition, the propagation probabilities were highest in autumn (0.71 ~ 0.89) and lowest in winter (0.41 ~ 0.62). The propagation probability increases as the meteorological drought evolved from summer to autumn, and the severe hydrological drought could be prevented by appropriate mitigation during that time.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.138-150
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• 2012

The purpose of this study was to examine the regional disparity of ambulatory health care utilization considering spatio-temporal variation in South Korea during 1996-2008(precisely, in 1996, 1999, 2002, 2005, and 2008) using bayesian hierarchial spatio-temporal model. The spatial pattern uses an intrinsic gaussian conditional autoregressive (CAR) error component. Ornstein-Uhlenbeck method was applied to detect the temporal patterns. The results showed that substantial temporal-geographical variation depending on diseases exists in Korea. On the Contrary to the pattern of total outpatient utilizations, for example, the areas that chronic diseases distributed relatively high were most in rural where the proportion of elderly population was higher than in the urban. Chungcheongnam-do, Junlabuk-do, and Kyeongsangbuk-do had higher risks in hypertension, whereas arthritis was higher risk in the Kyeonggi-do, Chungcheongbuk-do, Junlanam-do, and Junlabuk-do. The results of this study suggested that the effective health intervention programmes needed to alleviate the regional variation of health care utilization. These outcomes also provided the foundation for further investigation of risk factors and interventions in these high-risk areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.11-21
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• 2022

Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.184-184
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• 2020

수자원 계획 및 관리 시 증발산량의 정량적 분석은 필수적으로 고려되는 사항 중 하나이다. 일단위 이하의 잠재증발산량 산정은 세계식량기구(FAO)가 Penman-Monteith 방법을 기반으로 개발한 FAO56 PM 방법을 주로 활용하며, 이는 다른 방법에 비하여 높은 정확성과 적용성이 뛰어나다. 그러나 FAO56 PM 방법의 입력 매개변수는 다양한 기상자료이며, 장기간의 신뢰성 높은 자료를 구축하는 것은 어려운 실정이다. 이에 본 연구에서는 증발산량 공식인 Hargreaves 공식을 활용하여 FAO56 PM 방법으로 산정된 잠재증발산량과 기온차 사이의 시계열 관계를 재구성한 회귀분석 기법을 개발하였다. 개발된 모형에 유역면적을 적용하여 유역면적별 잠재증발산량을 산정하였으며, 이를 기존의 잠재증발산량과의 비교를 통해 모형의 적합성을 평가하였다. 결과적으로, 복잡한 잠재증발산량식을 단순한 대체모형(surrogate model)으로 제시함으로써 효율적인 증발산량 정량적 평가와 제한적인 기상자료 조건에 보편적 활용이 가능하다. 향후 연구에서는 회귀분석방법에 Bayesian 추론기법을 활용하여 구성함으로 잠재증발산량의 불확실성을 정량적으로 표현하고자 한다.