• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.45-60
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• 2014

We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Journal of the Korean Society of Safety
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• v.9 no.1
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• pp.89-94
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• 1994

Two methods, the numerical method of CPQRA and the manual method of IAEA, were used to estimate the effect distance from release and dispersion of toxic materials. The Gaussian plume model which has a weather stability class D with wind velocity of 5m/s was applied to calculate dispersion of toxic materials. Also, probit function were employed to evaluate the human fatality as a result of exposure to toxic gases. Furthermore, concentration of toxic materials corresponding to LC$_{50}$ for 30 min could be determined by setting Pr as 5.0 and solving the probit function. Calculations were conducted by employing chlorine and ammonia as toxic materials because they are not only most commonly used In chemical plants but also very harmful to humans. Calculated results by employing toxic materials indicated that the effect distance from the CPQRA method was between the minimum and maximum distance from the method proposed by IAEA.A.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.77-82
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• 2017

Thus, chemicals are managed under 9 related central government department and 16 relevant laws with program such as Process Safety Management and Offsite Consequence Analysis in korea. Guidelines for set the endpoint concentration for chemcals based on the ERPG-2 (Emergency Response Planning Guidelines-2) and AEGL-2 (Acute Exposure Guidelines Level-2). but ERPG and AEGL do not describe exposure for less than 10 minutes. because of this, each guidelines define criteria differently for short time less than 10 minutes exposure. This indefinite exposure criteria would give rise to a confusion in the chemical plants, and potentially lead to a critical decision making error when accidents happen. In an effort to apply guidelines with evenly-distributed initial time frame, AEGL concentrations within 10 minute exposure time were evaluated by examining statistical regression curves. The results were in good agreement with those from the Probit Function based on each AEGL grade to explain 3 different threshold levels of exposure effects. Resultant re-enforced guidelines for endpoint chemical concentrations are, therefore, to provide powerful tool to assess and manage the risk associated with any potential chemical accidents at an early stage.

• Environmental and Resource Economics Review
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• v.12 no.3
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• pp.469-485
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• 2003

This paper reports on the results of epidemiological investigation of daily health effects in the elderly associated with daily exposure to particulate matters in Korea. Our main focus is on the potential difference in health effects between PM10 and PM2.5. While the Korean environmental authority has set an ambient standard for PM10, the government currently does not monitor PM2.5, which has no national standard. A daily data on respiratory symptoms as well as PM concentrations are collected for a total of 120 days. Using a probit model, we find statistically significant negative health effects of PM2.5 on respiratory symptoms among the nonsmoking elderly, while PM10 does not show such effects from the estimation. This result suggests that, for air quality regulatory purposes, PM2.5 can be a more appropriate air pollutant than PM10.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.127-135
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• 2009

Most traffic information that drivers receive while driving are stored in their short-term memory and disappear within a few seconds. Contemporary modeling approaches using a dummy variable can't fully explain this phenomenon. As such, this study proposes to use utility functions of real-time in-vehicle traffic safety information (IVTSI), analyzing its safety impacts based on empirical data from an on-site driving experiment at signalized intersection approach with a limited visibility. For this, a driving stability evaluation model is developed based on driver's driving speed choice, applying an ordered probit model. To estimate the specified utility functions, the model simultaneously accounts for various factors, such as traffic operation, geometry, road environment, and driver's characteristics. The results show three significant facts. First, a normal density function (exponential function) is appropriate to explain the utility of IVTSI proposed under study over time. Second, the IVTSI remains in driver's short-term memory for up to nearly 22 second after provision, decreasing over time. Three, IVTSI provision appears more important than the geometry factor but less than the traffic operation factor.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.81-96
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• 2000

본 논문은 의학분야에서 주로 사용되는 메타분석 중 그룹화 임의효과 모형(grouped random effects model)을 프라빗 연결함수(probit link function)를 이용하여 베이즈적 관점에서 연구하였다. 이때 프라빗 함수를 강요하기 위해 잠재변수를 정의하였고, 사전 분포를 달리한 세가지 모형을 고려하였다. 주어진 세가지 모형들에게서 적합한 모형 선택을 위하여 베이즈 인자(Bayes factor, BF)와 유사베이즈 인자(pseudo-Bayes factor, PsBF)를 이용하였다. 깁스샘플러와 메트로폴리스 알고리즘을 이용하여 베이지안 계산상의 어려움을 해결하였다. 예로써, 새로운 간질약에 대한 효과를 조사하기 위하여 앞에서 제시된 방법으로 해석하였다.

• Journal of the Korean Home Economics Association
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• v.36 no.11
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• pp.209-218
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• 1998

The purpose of this study was to conduct the review of female labor suply, and thus, to provide useful theoretical and empirical frameworks for future studies related to female labor supply. Based on the theory of the allocation of time, the process of individual labor supply was systematically reviewed. Participation Probit/Logit, Tobit, and Selection B;ias Corrected Regression were considered in estimating the function of female labor supply which modifies the selection bias. Based on the previous empirical results, wage rate, asset income, husband's income, the level of eduction, and child-related variables such as the presence of child and the number of children might be considered for the empirical specification of female labor supply.

• Explosives and Blasting
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• v.37 no.4
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• pp.10-16
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• 2019

Information on overpressure, positive phase duration, and impulse are required to assess the effects of shock waves or pressure waves on the structure. In this study, the overpressure and positive phase duration were determined by applying the Multi-Energy Method, which is found to be effective in analyzing the explosion of vapor clouds. Based on the total heat of combustion estimated in the cyclohexane vapor cloud explosion in the Nypro Ltd(UK), overpressure and positive phase duration at the distance of 40, 80, 120, 160, 200, 240, 280, 320, 360(m) from the source of explosion were evaluated. Overpressure was shown to decrease exponentially and positive phase duration increased almost linearly with distance. A probit function was used to assess the probability of damages for the structures at each distance using the overpressure and impact obtained at the above mentioned distances. The Analyses of probability of damages have shown that there is a high probability of collapse at distances within 120m, major damage to structures within 240m, and minor damage and breakage of window panes of structures occur over the entire distances.