• The Korean Journal of Financial Studies
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• v.10 no.1
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• pp.1-44
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• 2004

연속시간모형은 시간의 흐름에 대응되는 자본자산의 운동의 성질과 시간의 흐름에 따라 형성되는 자본자산의 가격을 동시적으로 파악할 수 있는 것이 큰 장점이다. 연속시간 확률미분방정식을 구성하는 표류함수와 확산함수가 폐형해나 해석적 형태로 존재하지 않는 경우가 대부분이다. 여기에서 모수추정의 어려움이 발생한다. 전이 확률밀도함수의 인지 또는 발견의 어려움과 표류함수와 확산함수의 적분 불가능성은 최대가능도법의 사용을 어렵게 만든다. 여기에서 모수방법 보다는 비모수방법을 통하여 연속 확률 미분방정식을 추정하려는 성향이 존재한다. 밀도를 모르면 표본적률을 사용하여 모수를 추정할 수 있으므로 일반화 적률법이 연속시간 확률미분방정식의 모수 추정과 검정에 사용되고 있다. 전이밀도의 값을 시뮬레이션을 통하여 얻는 마코브연쇄 몬테카를로 방법, 전이밀도를 무한소 생성작용소를 통하여 얻는 방법, 비 모수방법, 여러 종류의 전개에 의하여 얻은 표류함수와 확산함수의 전이밀도에 대한 최대가능도법 등 여러 종류의 연속시간 확률미분방정식의 실증분석에서 사용되고 있다. 이 논문에서는 연속시간 확률미분방정식의 실증분석 방법들을 정리하는데 목적이 있다. 이일균(2004)은 이 논문과의 자매논문으로 시뮬레이션에 의한 확률미분방정식의 추정을 다루고 있어 시뮬레이션방법은 그 논문에 미룬다.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.373-385
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• 2007

The solution of the normal equation arising in a general linear model by the least square methods is not unique in general. Conventionally, SAS IML and G-inverse matrices are considered for such problems. In this paper, we provide a systematic solution procedures for SAS IML.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.407-426
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• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.148-148
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• 2011

Riemann 문제는 천수방정식과 같은 쌍곡선형 방정식과 단일한 도약에 의해 불연속인 어떤 점의 좌 우에서 상수인 자료로 구성되는 초기치 문제로서 그 해법은 Godunov 방법과 같이 정확해에 의하면 정확 Riemann 해법, 근사 기법에 의하면 근사 Riemann 해법으로 불린다. 지금까지 이용되는 근사 Riemann 해법으로는 1981년에 P. L. Roe가 제안한 Roe의 선형화 기법과 1983년에 A. Harten, P. D. Lax, 그리고 B. van Leer가 제안한 HLL 기법의 수정 기법들이다. 최대 및 최소 파속만 고려하는 것으로 알려진 HLL 기법은 1988년에 B. Einfeldt의 제안에 의해 두 파속의 결정에서 Roe의 선형화 기법에 따른 고유치와 비교하는 것으로 수정되었다(HLLE 기법). 또한, 1994년에 E. F. Toro 등은 접촉파를 고려하기 위해 선형화된 지배방정식의 정확해로부터 중앙 파속을 고려하는 기법을 제안하였고, 이를 HLLC 기법으로 불렀다. 2002년에 T. Linde는 중앙 파속을 평가하기 위해 일반화된(수학적) 엔트로피 함수를 도입하였으며, van Leer는 이를 HLLL 기법으로 불렀다. 이 기법에서는 접촉파의 평가를 위해 보존변수에 대한 일반화된 엔트로피 함수로부터 중앙 파속이 유도되며, 이것과 특성 속도의 비교를 통해 최대 및 최소 파속이 결정된다. 따라서 이 기법에서는 모든 파속이 초기치로부터 결정되므로 HLLE 기법과 달리 Roe의 선형화 기법과 완전히 결별되고 HLLC 기법과 달리 정확해에 의존되지 않는 점에서 HLLL 기법은 모태인 HLL 기법의 온전한 계승으로 볼 수 있다. HLLL 기법은 여러 분야에 적용된 바 있으나, 수공학 분야에 적용된 사례는 알려진 바 없다. 이는 천수방정식에 대한 (물리적) 엔트로피 함수가 명확하지 않기 때문인 것으로 보인다. 이 연구에서는 보존변수로부터 정의되는 총 에너지를 일반화된 엔트로피 함수로 간주하여 모형을 구성하고, 정확해가 알려진 1차원 문제에 대해 적용성을 검토하였다. 정확해가 알려진 경우에 대해 모의한 결과, 1차 정도 수치해의 한계에도 불구하고, HLLL 기법의 결과는 대체로 정확해와 잘 일치하였으며 그 외의 HLL-형 기법의 그것에 비해 우수한 것으로 나타났다. 특히, 물이 빠져 바닥이 드러나는 상태에 대한 접촉 파속의 추정에서 Riemann 불변량을 이용하는 HLLC 기법에 비해 물이 빠지는 전선을 더 정확하게 포착하는 HLLL 기법의 결과는 매우 고무적이었다.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.45-56
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• 2001

In this paper, we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations(GEEs) approach with the model-based approach through the design and weighting effects analysis.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.301-308
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• 2018

This study examined the relationship between transition in living arrangement and life satisfaction outcomes among older adults in Korea. This study utilized the secondary data of 2 waves(2005-2011) of a Korean Retirement and Income Study from the National Pension Research Institute. This study categorized living arrangement transition over time into 16 categories and used generalized the estimation equation(GEE) modeling to examine the relationship between living arrangement transition group membership and life satisfaction. The results showed that transition in living arrangement in old age was partly and significantly associated with life satisfaction in later life. In particular, the best living arrangement type in older adults in terms of life satisfaction was the coresidence with spouse compared with residence alone or residence with their children. The group of residence with their children was not related to higer satisfaction. More research is needed to explore the mechanism behind older people's trajectory in transition in living arrangement.

• Korean Journal of Agricultural Science
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• v.7 no.2
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• pp.131-144
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• 1980

The Linear Regression Model to extend the monthly runoff data in the short-recorded river was proposed by the author in 1979. Here in this study generalization precedure is made to apply that model to any given river basin and to any given station. Lengthier monthly runoff data generated by this generalized model would be useful for water resources assessment and waterworks planning. The results are as follows. 1. This Linear Regression Model which is a transformed water-balance equation attempts to represent the physical properties of the parameters and the time and space varient system in catchment response lumpedly, qualitatively and deductively through the regression coefficients as component grey box, whereas deterministic model deals the foregoings distributedly, quantitatively and inductively through all the integrated processes in the catchment response. This Linear Regression Model would be termed "Statistically deterministic model". 2. Linear regression equations are obtained at four hydrostation in Geum-river basin. Significance test of equations is carried out according to the statistical criterion and shows "Highly" It is recognized th at the regression coefficients of each parameter vary regularly with catchment area increase. Those are: The larger the catchment area, the bigger the loss of precipitation due to interception and detention storage in crease. The larger the catchment area, the bigger the release of baseflow due to catchment slope decrease and storage capacity increase. The larger the catchment area, the bigger the loss of evapotranspiration due to more naked coverage and soil properties. These facts coincide well with hydrological commonsenses. 3. Generalized diagram of regression coefficients is made to follow those commonsenses. By this diagram, Linear Regression Model would be set up for a given river basin and for a given station (Fig.10).

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.25-37
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• 2001

The marginal model is proposed for the analysis of data which have c(2: 3) categories in the 3 x 3 cross-over trials with three periods and three treatments. This model could be used for the counterpart of the Kenward-Jones' joint probability one and should be the generalization of Balagtas et ai's univariate marginal logits one, which analyze the treatment effects in the 3 x 3 cross-over trials with binary response variables[Kenward and Jones(1991), Balagtas et al(1995)]. The model equations for the marginal probability are constructed by the three types of link functions. The methods would be given for making of the link function matrices and model ones, and the estimation of parameters shall be discussed. The proposed model is applied to the analysis of Kenward and Jones' data.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.627-637
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• 2020

In this paper, the 1.24 million elderly patient medical data (HIRA-APS-2014-0053) provided by the Health Insurance Review and Assessment Service and weather data are analyzed with generalized estimating equation (GEE) model and long short term memory (LSTM) based recurrent neural network (RNN) model to predict the number of disease occurrence. To this end, we estimate the patient's residence as the area of the served medical institution, and the local weather data and medical data were merged. The status of disease occurrence is divided into three categories(occurrence of disease of interest, occurrence of other disease, no occurrence) during a week. The probabilities of categories are estimated by the GEE model and the RNN model. The number of cases of categories are predicted by adding the probabilities of categories. The comparison result shows that predictions of RNN model are more accurate than that of GEE model.

• Journal of Korean society of Dental Hygiene
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• v.20 no.6
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• pp.973-980
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• 2020

Objectives: This study was to analyz the effects of comparative evaluation of the effects of oil pulling on periodontal indices. Methods: A total subjects were 38; control group (19 subjects) and experimental group (19 subjects). In the experimental group, coconut oil was provided and rinsed the mouth for about 10 minutes once a day. We evaluated possession rate of pocket depth (≥4 mm), possession rate of bleeding on exploring and possession rate of gingival recession (≥1 mm). Results: The possession rate of pocket depth (≥4 mm), bleeding on exploring and gingival recession (≥1 mm) significant difference in interaction between the group and measurement time. Conclusions: The findings of this study indicate that dental hygiene process and oil pulling specialists in care of periodontal diseases were effective mediation.