• Computers and Concrete
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• v.6 no.1
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• pp.59-78
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• 2009

Reliability analysis for a proposed limit state bridge design code is performed. In order to introduce reliability concept to design code, the proposed live load model is based on truck weight survey. Test data of domestic material strengths are collected to model statistical properties of member strengths. Sample RC and PSC girder sections are designed following the safety factor format of the proposed code and compared with the current design practice. Reliability indexes are calculated and examined for material and member resistance factor formats and sample calibrations of safety factors are presented. It is concluded that the proposed code provides reasonable level of reliability compared to the international design standards.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.471-486
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• 2022

Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.21-35
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• 2023

Metabolic syndrome is a serious disease that can eventually lead to various complications, such as stroke and cardiovascular disease. In this study, we aimed to identify the risk factors related to metabolic syndrome for its prevention and recognition and propose a nomogram that visualizes and predicts the probability of the incidence of metabolic syndrome. We conducted an analysis using data from the Korea National Health and Nutrition Survey (KNHANES VII) and identified 10 risk factors affecting metabolic syndrome by using the Rao-Scott chi-squared test, considering the characteristics of the complex sample. A naïve Bayesian classifier was used to build a nomogram for metabolic syndrome. We then predicted the incidence of metabolic syndrome using the nomogram. Finally, we verified the nomogram using a receiver operating characteristic curve and a calibration plot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2672-2679
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• 2012

The study was done to provide basic data of medical quality evaluation after developing the comorbidity disease mortality measurement modeled on the severity-adjustment method of AMI. This study analyzed 699,701 cases of Hospital Discharge Injury Data of 2005 and 2008, provided by the Korea Centers for Disease Control and Prevention. We used logistic regression to compare the risk-adjustment model of the Charlson Comorbidity Index with the predictability and compatibility of our severity score model that is newly developed for calibration. The models severity method included age, sex, hospitalization path, PCI presence, CABG, and 12 variables of the comorbidity disease. Predictability of the newly developed severity models, which has statistical C level of 0.796(95%CI=0.771-0.821) is higher than Charlson Comorbidity Index. This proves that there are differences of mortality, prevalence rate by method of mortality model calibration. In the future, this study outcome should be utilized more to achieve an improvement of medical quality evaluation, and also models will be developed that are considered for clinical significance and statistical compatibility.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.383-389
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• 2011

In this paper, a statistical calibration method is proposed in order to identify the variability of complex modulus for a rubber material due to operational temperature and experimental/model errors. To describe temperature- and frequency-dependent material properties, a fractional derivative model and a shift factor relationship are used. A likelihood function is defined as a product of the probability density functions where experimental values lie on the model. The variation of the fractional derivative model parameters is obtained by maximizing the likelihood function. Using the proposed method, the variability of a synthetic rubber material is estimated and applied to a rubber mount problem. The dynamic characteristics of the rubber mount are calculated using a finite element model of which material properties are sampled from Monte Carlo simulation. The calculated dynamic stiffnesses show very large variation.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.619-630
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• 2019

Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4A
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• pp.323-329
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• 2011

Most current design codes of concrete structures adopt the partial safety factor format to assure the proper safety margin or reliability against various limit states as a practical design tool. The safety factors, load and resistance factors and so on, are determined based on the theory of structural reliability, which takes into account the statistical uncertainties of both loads and resistances. The establishment of statistical models for load and resistance should be preceded the application of reliability theory. In this paper, especially the influence of the statistical variations of resistance models, which are described in terms of strength of concrete, strength of reinforcements and sectional dimensions and so on, are examined and the probabilistic models for resistance of reinforced concrete members were developed. The statistical data were collected on local tests and experiments in Korea and the Monte Carlo simulation (MCS) technique was used. The results of this paper may be useful and valuable in calibration of design code in this country.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.131-157
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• 2018

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and taphonomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.107-114
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• 2005

The uncertainty of measurement in quantitative analysis of ammonia by continuous-flow analysis method was evaluated following internationally accepted guidelines. The sources of uncertainty associated with the analysis of ammonia were the weighing of sample, the preparation of extracting solution, the addition of extracting solution into the sample, the reproducibility of analysis and the determination of water content in tobacco, etc. In calculating uncertainties, Type A of uncertainty was evaluated by the statistical analysis of a series of observation, and Type B by the information based on supplier's catalogue and/or certificated of calibration. It was shown that the main source of uncertainty was caused by the volume measurement of 1 mL and 2 mL, the purity of ammonia reference material in the preparation of standard solution, the reproducibility of analysis and the determination of water content of tobacco. The uncertainty in the addition of extraction solution, the sample weighing, the volume measurement of 50 mL and 100 mL, and the calibration curve of standard solution contributed relatively little to the overall uncertainty. The expanded uncertainty of ammonia determination in burley tobacco at $95\%$ level of confidence was $0.00997\%$.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.726-735
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• 2003

A Process of 3-D Particle image velocimetry, called here, as '3-D volume PIV' was developed for the full-field measurement of 3-D complex flows. The present method includes the coordinate transformation from image to camera, calibration of camera by a calibrator based on the collinear equation, stereo matching of particles by the approximation of the epipolar lines, accurate calculation of 3-D particle positions, identification of velocity vectors by 3-D cross-correlation equation, removal of error vectors by a statistical method followed by a continuity equation criterior, and finally 3-D animation as the post processing. In principle, as two frame images only are necessary for the single instantaneous analysis 3-D flow field, more effective vectors are obtainable contrary to the previous multi-frame vector algorithm. An Experimental system was also used for the application of the proposed method. Three analog CCD camera and a Halogen lamp illumination were adopted to capture the wake flow behind a bluff obstacle. Among 200 effective particle s in two consecutive frames, 170 vectors were obtained averagely in the present study.