The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of ...The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.展开更多
Analysis of diarrhoea data in Malawi has been commonly done using classical methods. However, different approaches, such as Bayesian methods, have been introduced in literature. This study aimed at trying out semi-par...Analysis of diarrhoea data in Malawi has been commonly done using classical methods. However, different approaches, such as Bayesian methods, have been introduced in literature. This study aimed at trying out semi-parametric methods in comparison with classical ones, as well as how each isolates risk factors for child diarrhoea. This was done by fitting Logit, Poisson, and Bayesian models to 2006 Malawi Multiple Indicator Cluster Survey data. The comparison between Logit and Poisson models was done via chi-square＇s goodness-of-fit test. Confidence and Credible Intervals were used to compare Logit/Poisson and Bayesian model estimates. Modelling and inference in Bayesian method was done through MCMC techniques. The results showed agreement in significance and direction of estimates from Bayesian and Poisson/Logit models, but Poisson provided better fit than Logit model. Further, all the models identified child＇s age, breastfeeding status, region of stay and toilet-sharing status as significant factors for determining the child＇s risk. The models ruled out effects of mother＇s education, area of residence, and source of drinking water on the risk. Bayesian model separately proved significant closeness to lake/river factor. The findings imply that classical and semi-parametric models are equally helpful when estimating the child＇s risk to diarrhoea.展开更多
基金Project(71173061)supported by the National Natural Science Foundation of ChinaProject(2013U-6)supported by Key Laboratory of Eco Planning & Green Building,Ministry of Education(Tsinghua University),China
文摘The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.
文摘Analysis of diarrhoea data in Malawi has been commonly done using classical methods. However, different approaches, such as Bayesian methods, have been introduced in literature. This study aimed at trying out semi-parametric methods in comparison with classical ones, as well as how each isolates risk factors for child diarrhoea. This was done by fitting Logit, Poisson, and Bayesian models to 2006 Malawi Multiple Indicator Cluster Survey data. The comparison between Logit and Poisson models was done via chi-square＇s goodness-of-fit test. Confidence and Credible Intervals were used to compare Logit/Poisson and Bayesian model estimates. Modelling and inference in Bayesian method was done through MCMC techniques. The results showed agreement in significance and direction of estimates from Bayesian and Poisson/Logit models, but Poisson provided better fit than Logit model. Further, all the models identified child＇s age, breastfeeding status, region of stay and toilet-sharing status as significant factors for determining the child＇s risk. The models ruled out effects of mother＇s education, area of residence, and source of drinking water on the risk. Bayesian model separately proved significant closeness to lake/river factor. The findings imply that classical and semi-parametric models are equally helpful when estimating the child＇s risk to diarrhoea.
