• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.117-140
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• 1991

The purpose of this paper is primarily to introduce a nonparametric statistical tool developed by Baek and Brock to detect a unidirectional causal ordering between two economic variables and apply it to interesting macroeconomic relationships among money, production and prices. It can be applied to any other causal structure, for instance, defense spending and economic performance, stock market index and market interest rates etc. A key building block of the test for nonlinear Granger causality used in this paper is the correlation. The main emphasis is put on nonlinear causal structure rather than a linear one because the conventional F-test provides high power against the linear causal relationship. Based on asymptotic normality of our test statistic, the nonlinear causality test is finally derived. Size of the test is reported for some parameters. When it is applied to a money, production and prices model, some evidences of nonlinear causality are found by the corrected size of the test. For instance, nonlinear causal relationships between production and prices are demonstrated in both directions, however, these results were ignored by the conventional F-test. A similar results between money and prices are obtained at high lag variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1239-1247
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• 2010

In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The intensity function used Gompertz, Preto and Log-logstic pattern which has the efficient various property. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1903-1910
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• 2009

In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Korean Journal of Social Welfare Studies
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• no.39
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• pp.5-28
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• 2008

The purpose of this study is two-fold: 1) to identify different adolescent smoking trajectories in Korea; and 2) to examine predictors of those smoking trajectories within a social developmental frame. Data were from the Korea Youth Panel Survey(KYPS), a longitudinal study of 3,449 youths followed since 2003. Using semi-parametric group-based modeling, four smoking trajectories were identified: non initiators, late onsetters, experimenters, and escalators. Multinomial logistic regressions were then used to identify risk and protective factors that distinguish the trajectory groups from one another. Among non smokers at age 13, late onsetters were distinguished from non initiators by a variety of factors in every ecological domain. Among youths who already smoked at age 13, escalators who increased their smoking were distinguished from experimenters who almost desisted from smoking by age 17 by self-esteem and academic achievement. Finally, implications for youth welfare practice from this study were discussed.

• Journal of the Korea Society for Simulation
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• v.25 no.3
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• pp.117-123
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• 2016

This paper presents inference methods for inner operations of a multi-server queue when historical data are limited or system observation is restricted. In a queueing system analysis, autocorrelated arrival and service processes increase the complexity of modeling. Accordingly, numerous analysis methods have been developed. In this paper, we introduce an inference method for specific situations when external observations exhibit autocorrelated structure and and observations of internal operations are difficult. We release an assumption of the previous method and provide lemma and theorem to guarantee the correctness of our proposed inference method. Using only external observations, our proposed method deduces the internal operation of a multi-server queue via non-parametric approach even when the service times are autocorrelated. The main internal inference measures are waiting times and service times of respective customers. We provide some numerical results to verify that our method performs as intended.

• Journal of agriculture & life science
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• v.52 no.6
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• pp.37-47
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• 2018

The objective of this study was to analyze the influences of forest management activity on the diameter distribution of Larix kaempferi Carriere stands in South Korea. We used 232 managed stands data, 47 unmanaged stands data of National Forest Inventory for this study. We employed the Weibull distribution function for estimating diameter based on percentiles and parameter recovery method. The results revealed that the average diameter breast height movements and growth of tree in the managed stands higher than the unmanaged stands according to the scenario: age, site index, and tree density change. The finding shows the percentage of the total amount of large class diameter was also high in the managed stands. The results of this study could be apply for the estimation of multi-products of timbers per diameter classes and stand structure development for Larix kaempferi Carriere stands in South Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.88-88
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• 2023

지난 100년 동안 전 지구의 기상 이변이 꾸준히 증가하고 있다. 기후 변화는 도시 홍수 피해에 큰 영향을 끼치는데 급속한 도시화와 이상 기후로 인한 돌발 강우 패턴의 증가는 도시 침수의 취약성을 가중시킨다. 또한 급격한 도시 발전으로 인한 도심지의 불투수율 또한 꾸준히 증가하였다. 특히 2022년 8월 8일에 강남역과 도림천 일대에 내린 기록적인 강우는 기후 변화를 실감하게 하는 사회적 이슈가 되었으며 도심지 미래 수방 대책 변화를 상기시키는 계기가 되었다. 이로 인한 재해 피해에 최소화하기 위해 미래 기후 변화를 고려한 도심지의 새로운 방재 목표강우량 설정이 필요하다. 하지만 전 지구 모형(GCM)의 기후 변화 시나리오는 일 단위(Daily) 상세화 자료를 보편적으로 사용하고 있다. 하지만 이는 단기 강우 자료를 필요로 하는 도시 홍수 모의에서 제대로 활용할 수 없는 한계를 가지고 있다. 따라서 본 연구는 2019년에 발간된 IPCC 6차 평가 보고서(AR6)가 제안하는 SSP(Shared Socioeconomic Pathways, 공통사회경제경로) 시나리오를 기반하여 상세화된 일 단위(Daily) 강우 데이터를 비모수적 통계 기법을 사용하여 시간 단위(Hourly)로 상세화하였다. 또한 지속 시간별 연 최대치 강우를 추출하여 빈도 해석을 통해 도시 유역의 미래 확률 강우량을 제시하였으며, 서울시 상습적인 침수 취약 지역인 도림천 유역에 강우-유출 모형(XP-SWMM)을 사용하여 미래전망 기후 자료인 SSP2-4.5와 SSP5-8.5에 따른 미래 확률 강우 침수 모의를 실시하였다. 본 연구의 결과는 최신 기후 변화 시나리오를 고려한 서울시 방재 성능 목표 강우량 산정에 활용 가능할 것으로 사료되며 미래 강우량 침수 모의를 통해 침수 취약 구역인 도림천 일대 홍수피해의 근거 자료가 되는 것에 의의를 둔다. 또한 치수 분야에서 기후 변화를 고려하기 위해서는 기후 변화 시나리오에 따른 시간 단위 자료의 상세화가 필요함을 시사한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.479-485
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• 2017

This study estimated the non-use values of the Gum river estuary which are not related to the direct or indirect use of the Gum river estuary using the contingent valuation method (CVM). The non-use values of the Gum river estuary were explained and asked to be evaluated in the CVM questionnaire and estimates of the WTPs(willingness-to-pay) were elicited using the Turnbull nonparametric estimation methods on the dichotomous choice CV data. Results found the Turnbull lower bounded mean WTP per year for non-use value of the Gum river estuary was estimated at 5,822 won (95% C.I. 5,295 ~ 6,349 won) from single dichotomous CV data, and 6,205 won (95% C.I. 5,701 ~ 6,710 won) from double dichotomous CV data. The mean of two WTP estimates, 6,014 won (95% C.I. 5,498 ~ 6,529 won), was used to calculate the annual total non-use value of the Gum river estuary. Therefore, the non-use value of the Gum river estuary was estimated at 220.3 billion won (95% C.I. 201.4 - 239.2 billion won) annually. This non-use value of the Gum river estuary was composed of the bequest value totaling 68.3 billion won (95% C.I. 62.5 - 74.2 billion won), the existence value of 58.0 billion won (95% C.I. 53.0 - 63.0 billion won), the option value of 57.7 billion won (95% C.I. 52.7 - 62.6 billion won), and the vicarious consumption value totaling 36.3 billion won (95% C.I. 33.1 - 39.4 billion won).

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.1-12
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• 2006

The aim of this study is to analyse a survey data on the number of charitable donations using a mixture of two Poisson regression models. The survey was conducted in 2002 by Volunteer 21, an nonprofit organization, based on Koreans, who were older than 20. The mixture of two Poisson distributions is used to model the number of donations based on the empirical distribution of the data. The mixture of two Poisson distributions implies the whole population is subdivided into two groups, one with lesser number of donations and the other with larger number of donations. We fit the mixture of Poisson regression models on the number of donations to identify significant covariates. The expectation-maximization algorithm is employed to estimate the parameters. We computed 95% bootstrap confidence interval based on bias-corrected and accelerated method and used then for selecting significant explanatory variables. As a result, the income variable with four categories and the volunteering variable (1: experience of volunteering, 0: otherwise) turned out to be significant with the positive regression coefficients both in the lesser and the larger donation groups. However, the regression coefficients in the lesser donation group were larger than those in larger donation group.