• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.29-29
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• 2023

To mitigate the damaging impacts of floods, accurate prediction of runoff, streamflow and flood inundation is needed. Conventional approach of simulating hydrology and hydraulics using loosely coupled models cannot capture the complex dynamics of surface and sub-surface processes. Additionally, the scarcity of data in ungauged basins and quality of data in gauged basins add uncertainty to model predictions, which need to be quantified. In this presentation, first the role of integrated modeling on creating accurate flood simulations and inundation maps will be presented with specific focus on urban environments. Next, the use of machine learning in producing streamflow predictions will be presented with specific focus on incorporating covariate shift and the application of theory guided machine learning. Finally, a framework to quantify the uncertainty in flood models using Hierarchical Bayesian Modeling Averaging will be presented. Overall, this presentation will highlight that creating accurate information on flood magnitude and extent requires innovation and advancement in different aspects related to hydrologic predictions.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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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.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.30.3-30.3
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• 2021

In order to generate the 3D structure of the 21-cm signal during the reionization, semi-numerical simulations based on Excursion set formalism are broadly used. However, semi-numerical simulations in the realization of the 3D structure are known to be the ionizing photon non-conserving by the structure of the Excursion set approach. Recently, explicit photon conserving algorithms for semi-numerical simulations introduced, but they are still too slow when forward modelling the 21-cm signal with high-dimensional parameter spaces. Here, we introduce a new method for approximately correcting photon non-conservation, which can be applied on-the-fly. This method is tailored towards the efficient simulation and Bayesian inference with high-dimensional parameter space. Then, we investigate how large an impact that photon non-conservation has on astrophysical parameter inference by performing an MCMC analysis. We find that the ionizing escape parameter is deviated from the fiducial value by 2 sigma when we infer astrophysical parameters without this correction.

• Journal of Arbitration Studies
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• v.33 no.3
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• pp.129-146
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• 2023

We construct a signaling game model between the arbitrator and claimants, in which the arbitrator's marketing amount is adopted as the signaling device. Assuming that the parties to the dispute select an arbitrator, and if there is a difference in the arbitrator's fee depending on the arbitrator's reputation, the arbitrator will pay to further enhance his reputation. We would like to analyze the cost differences between arbitrators who already have a high reputation and arbitrators who strive to further enhance their reputation using the signal model. From the Analysis of our study, We derive perfect Bayesian equilibrium of the signaling game and refine the equilibrium into a unique equilibrium by invoking the Intuitive Criterion of Cho and Kreps (1987). Further, we characterize the refined equilibrium.

• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.427-440
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• 2024

The problem addressed is that of sequentially estimating the difference between the means of two populations with respect to the squared error loss, where each population distribution is a member of the one-parameter exponential family. A Bayesian approach is adopted in which the population means are estimated by the posterior means at each stage of the sampling process and the prior distributions are not specified but have twice continuously differentiable density functions. The main result determines an asymptotic second-order lower bound, as t → ∞, for the Bayes risk of a sequential procedure that takes M observations from the first population and t - M from the second population, where M is determined according to a sequential design, and t denotes the total number of observations sampled from both populations.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1457-1469
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• 2017

Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.8
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• pp.1085-1090
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• 2002

Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.

• Korean Journal of Plant Taxonomy
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• v.49 no.2
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• pp.118-126
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• 2019

The taxonomic rank of the tiny-leaved terrestrial orchid Cephalanthera subaphylla Miyabe & $Kud{\hat{o}}$ has been somewhat controversial, as it has been treated as a species or as an infraspecific taxon, under C. erecta (Thunb.) Blume [C. erecta var. subaphylla (Miyabe & $Kud{\hat{o}}$) Ohwi and C. erecta f. subaphylla (Miyabe & $Kud{\hat{o}}$) M. Hiro]. Allozyme markers, traditionally employed for delimiting species boundaries, are used here to gain information for determining the taxonomic status of C. subaphylla. To do this, we sampled three populations of five taxa (a total of 15 populations) of Cephalanthera native to the Korean Peninsula [C. erecta, C. falcata (Thunb.) Blume, C. longibracteata Blume, C. longifolia (L.) Fritsch, and C. subaphylla]. Among 20 putative loci resolved, three were monomorphic (Dia-2, Pgi-1, and Tpi-1) across the five species. Apart from C. longibracteata, there was no allozyme variation within the remaining four species. Of the 51 alleles harbored by these 17 polymorphic loci, each of the 27 alleles at 14 loci was unique to a single species. Accordingly, we found low average values of Nei's genetic identities (I) between ten species pairs (from I = 0.250 for C. erecta versus C. longifolia to I = 0.603 for C. falcata vs. C. longibracteata), with C. subaphylla being genetically clearly differentiated from the other species (from I = 0.349 for C. subaphylla vs. C. longifolia to 0.400 for C. subaphylla vs. C. falcata). These results clearly indicate that C. subaphylla is not genetically related to any of the other taxa of Cephalanthera that are native to the Korean Peninsula, including C. erecta. In a principal coordinate analysis (PCoA), C. subaphylla was positioned distant not only from C. falcata, C. longibracteata, and C. longifolia, but also from C. erecta. Finally, K = 5 was the best clustering scheme using a Bayesian approach, with five clusters precisely corresponding to the five taxa. Thus, our allozyme results strongly suggest that C. subaphylla merits the rank of species.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1133-1140
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• 2013

A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.