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Full-Text Articles in Physical Sciences and Mathematics
Outlier-Resistant Models For Doubly Stochastic Point Processes, Leo Stephan Elsaesser
Outlier-Resistant Models For Doubly Stochastic Point Processes, Leo Stephan Elsaesser
Theses and Dissertations
This thesis proposes an outlier-resistant multiplicative component model for doubly stochastic point processes. The model is based on a principal component decomposition of the log-intensity functions, using heavy-tailed t-distributions for the component scores. As an example of application, the temporal distribution of bike check-out times in the Divvy bike sharing system of Chicago is analyzed using the t-model.
A Statistical Model For The Influence Of Temperature On Bike Demand In Bike-Sharing Systems, Tobias Tietze
A Statistical Model For The Influence Of Temperature On Bike Demand In Bike-Sharing Systems, Tobias Tietze
Theses and Dissertations
Efficient fleet management is essential for bike-sharing systems. Thus, it is important to understand the impact of environmental factors on bike demand. This thesis proposes a method to analyze the influence of temperature on bike demand. Hourly temperature data are approximated by smoothed curves and modeled by functional principal components. Bike check-out times, which can be seen as realizations of a doubly stochastic process, are modeled using multiplicative component models on the underlying intensity functions. The respective component scores are then related via a multivariate regression model. An analysis of data from the Divvy system of the City of Chicago …
A Statistical Model For The Influence Of Temperature On Bike Demand In Bike-Sharing Systems, Tobias Tietze
A Statistical Model For The Influence Of Temperature On Bike Demand In Bike-Sharing Systems, Tobias Tietze
Theses and Dissertations
Efficient fleet management is essential for bike-sharing systems. Thus, it is important to understand the impact of environmental factors on bike demand. This thesis proposes a method to analyze the influence of temperature on bike demand. Hourly temperature data are approximated by smoothed curves and modeled by functional principal components. Bike check-out times, which can be seen as realizations of a doubly stochastic process, are modeled using multiplicative component models on the underlying intensity functions. The respective component scores are then related via a multivariate regression model. An analysis of data from the Divvy system of the City of Chicago …
Outlier-Resistant Models For Doubly Stochastic Point Processes, Leo Stephan Elsaesser
Outlier-Resistant Models For Doubly Stochastic Point Processes, Leo Stephan Elsaesser
Theses and Dissertations
This thesis proposes an outlier-resistant multiplicative component model for doubly stochastic point processes. The model is based on a principal component decomposition of the log-intensity functions, using heavy-tailed t-distributions for the component scores. As an example of application, the temporal distribution of bike check-out times in the Divvy bike sharing system of Chicago is analyzed using the t-model.
Identifying And Incorporating Driver Behavior Variables Into Crash Prediction Models, Mohammad Razaur Rahman Shaon
Identifying And Incorporating Driver Behavior Variables Into Crash Prediction Models, Mohammad Razaur Rahman Shaon
Theses and Dissertations
All travelers are exposed to the risk for crashes on the road, as none of the roadways are entirely safe. Under Vision Zero, improving traffic safety on our nation’s highways is and will continue to be one of the most pivotal tasks on the national transportation agenda. For decades, researchers and transportation professionals have strived to identify causal relationships between crash occurrence and roadway geometry, and traffic-related variables on the mission of creating a safe environment for the traveling public. Although great achievements have been witnessed such as the publication of the Highway Safety Manual (HSM), research is rather limited …