• Title/Summary/Keyword: discrete change in probability

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Marginal Effect Analysis of Travel Behavior by Count Data Model (가산자료모형을 기초로 한 통행행태의 한계효과분석)

  • 장태연
    • Journal of Korean Society of Transportation
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    • v.21 no.3
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    • pp.15-22
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    • 2003
  • In general, the linear regression model has been used to estimate trip generation in the travel demand forecasting procedure. However, the model suffers from several methodological limitations. First, trips as a dependent variable with non-negative integer show discrete distribution but the model assumes that the dependent variable is continuously distributed between -$\infty$ and +$\infty$. Second, the model may produce negative estimates. Third, even if estimated trips are within the valid range, the model offers only forecasted trips without discrete probability distribution of them. To overcome these limitations, a poisson model with a assumption of equidispersion has frequently been used to analyze count data such as trip frequencies. However, if the variance of data is greater than the mean. the poisson model tends to underestimate errors, resulting in unreliable estimates. Using overdispersion test, this study proved that the poisson model is not appropriate and by using Vuong test, zero inflated negative binomial model is optimal. Model reliability was checked by likelihood test and the accuracy of model by Theil inequality coefficient as well. Finally, marginal effect of the change of socio-demographic characteristics of households on trips was analyzed.

Development of Snow Depth Frequency Analysis Model Based on A Generalized Mixture Distribution with Threshold (최심신적설량 빈도분석을 위한 임계값을 가지는 일반화된 혼합분포모형 개발)

  • Kim, Ho Jun;Kim, Jang-Gyeong;Kwon, Hyun-Han
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.4
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    • pp.25-36
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    • 2020
  • An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.

Development of Social Work Strategies for School-linked services - Based on Latent Class Growth Analysis of Delinquent Behaviors in adolescence - (학교연계 서비스를 위한 사회복지실천 전략 개발 - 청소년기 경비행행동의 차별적 발달궤적에 대한 잠재계층성장분석 -)

  • Lee, Sang-Gyun
    • Korean Journal of Social Welfare Studies
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    • v.40 no.3
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    • pp.377-406
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    • 2009
  • This study used laten class growth analysis to identify discrete developmental patterns of delinquent behaviors in adolescence. This present article also examined associations among these trajectories to determine how the development of delinquent behaviors relates to protective and risk factors, which include parental monitoring, attachment with parent, association with deviant peers, self-control, and negative stigma from others. Four-wave panel data from a Korea Youth Panel Study were used for the latent class growth model analysis. The sample consisted of 3,446 adolescents who were assessed at 4 measurement waves with approximately 1-year interval. Four trajectories of delinquent behaviors emerged: delinquency persistence, delinquency increaser, delinquency decreaser, normative group(almost no delinquent behaviors). Association with deviant peers had the most proximal strong influence on the probability of being in the delinquency increaser and delinquency persistence group compared, noed to the normative group. Parental monitoring, self-efficacy and negative stigma also differentiated the four delinquent behavior trajectories from one another after controllig for socio-demographic variables. The study suggested that there is a significant heterogeneity in the timing and change rate of delinquency progression. Adolescent delinquency prevention and intervention programs will need to consider this heterogeneity and enhance attention to protective and risk factors depending on the subpopulation.