• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.683-699
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• 2007

This study applied the choice experiment (CE) method to measure values of statistical lives from multi-attributed mortality risk reduction choices. The four characteristics of mortality risk (i.e. cause of death, voluntariness of mortality risk, timing of death, magnitude of mortality risk reduction) are utilized to design the alternatives of choice sets. The estimation results for the multinomial logit model show that individuals are willing to pay 27,930 won per year for a change from the status quo to a $\frac{1}{100}$ mortality risk reduction for 10 years, 116,773 won per year for mortality risk reduction associated with adults, 97,682 won per year for voluntary mortality risk reduction, 77,234 won per year for involuntary mortality risk reduction. There were several estimates of VSL related to different attributes of mortality risk. The mean VSLs of infant/child/young adult ranged from 1,165 million won to 1,367 million won. The mean VSLs ranged from 1,631 million won to 1,833 million won for adult, and were between 1,128 million won and 1,330 million won for old person.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.87-100
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• 2000

각 지역특성에 맞는 ATIS사업이 실현되기 위해서는 각 지역 통행자들의 노선선택 및 전환행태를 정확히 파악하는 것이 필요하다. 이에 본 연구에서는 경상대를 연구대상으로 하여 대학출근운전자들의 노선선택 및 전환 행태를 정확히 파악하고 이들을 모형화하였다. 본 연구 대상지의 경우, 2개의 주 출근노선이 있으며 하나는 시내통행노선(노선 1)이고 다른 하나는 시외곽 통행노선(노선 2)이다. 노선1은 노선2에 비해 연장은 짧은 반면에 통행시간은 길며 신호교차로수. 우회전수도 많다. 먼저, 운전자의 노선선택행태모형을 통해 해석된 결과를 보면 시내노선에 대한 외곽노선의 상대적 효용이 아주 높으며, 전체적으로 출근운전자들은 짧은 통행시간을 선호하는 것으로 나타났다. 또한, 출근소요시간이 길고 라디오정보의 이용빈도가 높을수록 시내노선을 이용할 확률이 크며, 반면에 남성과 교직원인 운전자는 외곽노선을 이용할 확률이 큰 것으로 나타났다. 다음으로 행태조사에 기초한 노선전환행태모형을 통해 해석된 결과를 보면 연령, 출근시간, 라디오정보의 이용빈도들이 전환성향에 유의한 영향을 가져오는 것으로 분석되었다. 가상의 교통정보제공시의 운전자의 노선전환을 모형화한 노선전환의사모형에서는 대개의 정보에 대해 운전자가 노선전환을 하는 것으로 나타났다. 이 모형에서 지체길이에 따른 전환경향을 보면 지체의 길이가 길수록 전환경향이 높아 30분정도의 지체길이에서는 반드시 변경하는 것으로 나타났다. 본 연구대상 운전자의 경우 전반적으로 기술적인 유고(Incident)정보보다는 정량적인 지체정보에 더 민감한 것으로 나타났다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.881-891
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• 2014

Graphical models can be used as an intuitive tool for modeling a complex stochastic system with a large number of variables related each other because the conditional independence between random variables can be visualized as a network. Graphical least absolute shrinkage and selection operator (LASSO) is considered to be effective in avoiding overfitting in the estimation of Gaussian graphical models for high dimensional data. In this paper, we consider the model selection problem in graphical LASSO. Particularly, we compare various model selection criteria via simulations and analyze a real financial data set.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.439-449
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• 2020

Meta-analysis provides a way of integrating several independent studies of interest. Since small studies with statistically significant results are more likely to be published, publication bias, which is a special case of selection bias, often occurs in meta analysis. Conditional likelihood and weighted estimating equation have been proposed to deal with publication bias, but they require to specify a correct selection probability model. In contrast, the pairwise pseudolikelihood approach can correct publication bias without fully specifying the correct selection probability model, but its performance in meta-analysis was not investigated. In this paper, we perform a numerical study about whether the pairwise pseudolikelihood approach is effective for solving publication bias arising from typical meta-analysis settings.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.909-922
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• 2019

In this paper, we study the adaptive least absolute shrinkage and selection operator (LASSO) for the unstable autoregressive (AR) model. To identify the existence of the unit root, we apply the adaptive LASSO to the augmented Dickey-Fuller regression model, not the original AR model. We illustrate our method with simulations and a real data analysis. Simulation results show that the adaptive LASSO obtained by minimizing the Bayesian information criterion selects the order of the autoregressive model as well as the degree of differencing with high accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.104-104
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• 2012

최근 기후변화에 의하여 기상현상이 급변하고 있는 추세이며 강우사상의 경향 또한 그러한 변화를 따라가고 있다. 이러한 시점에서 극적인 강우사상에 대하여 대비해야 할 필요성이 대두되고 있으며 빈도해석을 통하여 확률강우량을 제시하는 방법이 연구되고 많은 발전을 거듭하고 있다. 이러한 방법은 모든 설계에 대하여 보편적으로 적용되고 있지만 일변량 빈도해석을 통하여 얻게 되는 확률량(Quantile)은 한 가지 자료계열에 대하여서만 고려할 수 있다. 이러한 단점을 극복하기 위하여서는 다변량 빈도해석을 수행하는 방법이 있으며 이 또한 국내외적으로 활발히 연구되고 있는 분야이다. 본 연구에서는 이변량 빈도해석을 수행하기 위해 3가지의 copula 모형을 선택하였으며 강우량과 강우지속시간을 자료계열로 사용하여 이변량 빈도해석을 수행하였다. 이를 통하여 얻은 확률강우량을 기존의 일변량 빈도해석의 결과와 정량적으로 비교하여 그 결과를 비교 분석하였으며 향후 새로운 빈도해석 방법의 가능성 및 적절성을 판단하고자 하였다.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.281-301
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• 2004

In this paper we consider the change point problem in a sequence of univariate normal observations. We want to know whether there is any change point or not. In case a change point exists, we will identify its change type. Namely, it can be a mean change, a variance change, or both the mean and variance change. The intrinsic Bayes factors of Berger and Pericchi (1996, 1998) are used to find the type of optimal change model. The Gibbs sampling including the Metropolis-Hastings algorithm is used to estimate all the parameters in the change model. These methods are checked via simulation and applied to the winter average temperature data in Seoul.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.61-78
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• 2017

Among several policies for industrial decentralization introduced since the 1960s, business relocation grant policies put a heavy financial burden on central and local governments. This study investigates the change in the likelihood of manufacturing establishments' relocation to the non-SMA associate with the change in business relocation grant policies. Using the mining and manufacturing survey data from 1996 to 2014, manufacturing firms' relocation decision model in nested logit structure was estimated. The data showed that the proportion of movements from the SMA to the non-SMA significantly increased after the introduction of the grant policies. However, estimation results of firms' relocation decision model indicated that the likelihood of firms relocating from the SMA to the non-SMA decreased after the introduction of the grant policies. In particular, firms' likelihood to move into the rural regions is even lower in the period of the grant extension. This suggests that increasing rate of relocations toward the rural regions may have been driven by the growing advantage of rural locations, such as low land rent and improvement in market accessibility, rather than the grants per se. This implies that the alleviation of physical and environmental constraints of the rural regions and the creation of business friendly environment such as easy access to premises at reasonable prices and strengthened linkage with the SMA, rather than simple provision of business relocation grants, needed to attract businesses in the rural regions.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.145-159
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• 1996

다변량 발병시간자료는 각 개개 환자에게 있어 합병증이 발생되거나 혹은 유사 환자군(집락) 내의 발병시간이 상관되어진 생의학자료에서 흔히 볼 수 있다. HMULCOX는 그런 자료를 분석하기 위한 한글 통계 패키지 가운데 하나이다. 이 프로그램은 관련된 발병시간들이 독립이 아닐때에도 COX 비례 위험 모형의 주변확률분포를 계산해 준다. 주어진 조건으로는 주변확률모형의 기본위험율은 일정한 상수, 흑은 변수라도 관계없다. 또한 치료실패율의 치료변수들(공변량)의 효과에 대해 다양한 통계적 추론이 가능하다. 기본적으로 주변확률분포접근법으로 설계되었지만 HMULCOX는 여러 가지 추론 방법을 선택하는 데 일반적으로 충분하다. 이 프로그램으로 2개의 예를 들어 실행하겠다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1099-1107
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• 2017

In this study, we analyzed the determinants of wages of college graduates by using the data of "2014 Graduates Occupational Mobility Survey" conducted by Korea Employment Information Service. In general, wages contain two complex pieces of information about whether an individual is employed and the size of the wage. However, in many previous researches on wage determinants, sample selection bias tends to be generated by performing linear regression analysis using only information on wage size. We used the Heckman sample selection models for analysis to overcome this problem. The main results are summarized as follows. First, the validity of the Heckman's sample selection model is statistically significant. Male is significantly higher in both job probability and wage than female. As age increases and parents' income increases, both the probability of employment and the size of wages are higher. Finally, as the university satisfaction increases and the number of certifications acquired increased, both the probability of employment and the wage tends to increase.