• Title/Summary/Keyword: 밀도추정모형

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Density Predictive Model within the On-Ramp Merge Influence Areas of Urban Freeway - Based on the Beonyoungro in the Metropolitan City of Busan - (도시고속도로의 유입연결로 합류영향권내 밀도추정모형 구축에 관한 연구 -부산광역시 번영로를 대상으로 -)

  • Kim, Tae Gon;Pyo, Jong Jin;Kwon, Mi Hyun;Jo, In Kook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3D
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    • pp.287-293
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    • 2008
  • Density is used as the measure of effectiveness within the ramp junction influence area suggested in the KHCM 2005 in the LOS analysis of the ramp junction, and also density predictive models suggested in the KHCM 2005 is constructed based on the expressway with the speed limit of 100km/h or 110km/h in Korea. So, the density predictive models suggested in the KHCM 2005 are needed to verify if the models could be applied to the urban freeway with the speed limit of 80km/h or less, because the speed limits on most of the urban freeways in Korea are 80km/h or less. The purpose in this study is to construct and verify the appropriate density predictive model within the on-ramp merge influence area of the urban freeway by comparing with the USHCM 2000 and KHCM 2005 models.

Likelihood Approximation of Diffusion Models through Approximating Brownian Bridge (브라운다리 근사를 통한 확산모형의 우도 근사법)

  • Lee, Eun-kyung;Sim, Songyong;Lee, Yoon Dong
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.895-906
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    • 2015
  • Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

Truncation Parameter Selection in Binary Choice Models (이항 선택 모형에서의 절단 모수 선택)

  • Kim, Kwang-Rae;Cho, Kyu-Dong;Koo, Ja-Yong
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.811-827
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    • 2010
  • This paper deals with a density estimation method in binary choice models that can be regarded as a statistical inverse problem. We use an orthogonal basis to estimate density function and consider the choice of an appropriate truncation parameter to reflect the model complexity and the prediction accuracy. We propose a data-dependent rule to choose the truncation parameter in the context of binary choice models. A numerical simulation is provided to illustrate the performance of the proposed method.

The Linear Density Predictive Models on the On-Ramp Junction in the Urban Freeway (도시고속도로의 진입연결로 접속부내 선형의 밀도예측모형 구축에 관한 연구)

  • Kim, Tae Gon;Shin, Kwang Sik;Kim, Seung Gil;Kim, Jeong Seo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.59-66
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    • 2006
  • This study was to construct the linear density predictive models on the on-ramp junctions in urban freeway. From the analyses of the real-time traffic characteristic data, and the construction and verification of the linear density predictive models, the models showed a considerable explanatory power with the determination coefficients ($R^2$) of over 0.7 between the density and speed data. Also, they showed a considerably high correlativeness with the correlation coefficients (r) of over 0.8 between the calculated density data and the expected ones estimated by the models.

Test for Distribution Change of Dependent Errors (종속 오차에 대한 분포 변화 검정법)

  • Na, Seong-Ryong
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.587-594
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    • 2009
  • In this paper the change point problem of the error terms in linear regression models is considered. Since fixed or stochastic independent variables and weakly dependent errors are assumed, usual multiple regression models and time series models including ARMA are covered. We use the estimates of probability density function based on residuals in order to test the distribution change of the unobserved errors. Under some mild conditions, the test using the residuals is proved to have the same limiting distribution as the test based on true errors.

Density estimation of summer extreme temperature over South Korea using mixtures of conditional autoregressive species sampling model (혼합 조건부 종추출모형을 이용한 여름철 한국지역 극한기온의 위치별 밀도함수 추정)

  • Jo, Seongil;Lee, Jaeyong
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1155-1168
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    • 2016
  • This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.

An Estimation of Congestion Pricing Using Speed-Flow Relationship (Gangbyeon Expressway) (속도-밀도 모형을 적용한 흔잡통행료 산정 (강변북로를 중심으로))

  • Gang, Gyeong-U;Guk, U-Gak
    • Journal of Korean Society of Transportation
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    • v.24 no.2 s.88
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    • pp.31-41
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    • 2006
  • The main purpose of this paper is to develop the practical method to estimate the congestion price in odor to overcome the difficulty of traditional microeconomics approach for demand and cost function concepts. In this paper, we estimate the theoretical congestion toll which reflecting the real traffic conditions such as a speed-density functions using a traffic engineering methods We calculates the optimal congestion toll based on the real traffic conditions assuming that the electronic road pricing (ERP) systems ave installed for the study road. After evaluating the various speed-density relationship methods. we found that the Drake model is best suited for the Gangbyeon Expressway Using the Drake model, the optimal congestion toll will be 94 to 3,255 Won for the traffic speed between 44km/h to 68 km/h based on wage rate method and 107 to 6,381 Won for the marginal substitution method for the Gangbyeon Expressway in city of Seoul, Korea.

Analysis of Characteristics of the Dynamic Flow-Density Relation and its Application to Traffic Flow Models (동적 교통량-밀도 관계의 특성 분석과 교통류 모형으로의 응용)

  • Kim, Young-Ho;Lee, Si-Bok
    • Journal of Korean Society of Transportation
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    • v.22 no.3 s.74
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    • pp.179-201
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    • 2004
  • Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed dynamically and interpreted as a states diagram. The dynamic flow-density relation is quantified by applying fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.

A Brief Review of a Term Saddlepoint Approximation Method for Estimating Diffusion Processes (단일항 안장점근사법에 의한 확산모형의 추정)

  • Lee, Eun-Kyung;Lee, Yoon-Dong;Choi, Young-Soo
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.367-376
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    • 2010
  • Recently various methods were suggested and reviewed for estimating diffusion processes. Out of suggested estimation method, we mainly concerns on the estimation method using saddlepoint approximation method, and we suggest a term saddlepoint approximation(ASP) method which is the simplest saddlepoint approximation method. We will show that ASP method provides fast estimator as much as Euler approximation method(EAM) in computing, and the estimator also has good statistical properties comparable to the maximum likelihood estimator(MLE). By simulation study we compare the properties of ASP estimator with MLE and EAM, for Ornstein-Uhlenbeck diffusion processes.

Application for a BWIM Algorithm Using Density Estimation Function and Average Modification Factor in The Field Test (밀도추정함수와 평균보정계수를 이용한 BWIM 알고리즘의 현장실험 적용)

  • Han, Ah Reum Sam;Shin, Soobong
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.15 no.2
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    • pp.70-78
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    • 2011
  • The paper aims at developing a more reliable and accurate BWIM(Bridge Weigh-In-Motion) algorithm using measured strain data and examining its efficiency with various tests on bridges. It proposes a BWIM algorithm using density estimation function and average modification factor for moment-strain relationship. Density estimation function has been proved to be reliably applied when multiple axle loads are estimated. An average modification factor is applied to minimize overall error that can be encountered between theoretically computed moments and measured strains at multiple locations in a bridge. The developed algorithm has been successfully examined through numerical simulations, laboratory tests, and also by field tests on a multi-girder composite bridge.