10 citations · 22 across the 12 of their papers we have counts for
13 papers
Causal inference for data centric engineering
Daniel J Graham
The paper reviews methods that seek to draw causal inference from observational data and demonstrates how they can be applied to empirical problems in engineering research. It pres…
Face masks, vaccination rates and low crowding drive the demand for the London Underground during the COVID-19 pandemic
Prateek Bansal, Roselinde Kessels, Rico Krueger +1
The COVID-19 pandemic has drastically impacted people's travel behaviour and out-of-home activity participation. While countermeasures are being eased with increasing vaccination r…
Revisiting the empirical fundamental relationship of traffic flow for highways using a causal econometric approach
Anupriya, Daniel J. Graham, Daniel Hörcher +1
The fundamental relationship of traffic flow is empirically estimated by fitting a regression curve to a cloud of observations of traffic variables. Such estimates, however, may su…
Non-parametric Bayesian inference via loss functions under model misspecification
Yu Luo, David A. Stephens, Daniel J. Graham +1
In the usual Bayesian setting, a full probabilistic model is required to link the data and parameters, and the form of this model and the inference and prediction mechanisms are sp…
Willingness to Pay and Attitudinal Preferences of Indian Consumers for Electric Vehicles
Prateek Bansal, Rajeev Ranjan Kumar, Alok Raj +2
Consumer preference elicitation is critical to devise effective policies for the diffusion of electric vehicles (EVs) in India. This study contributes to the EV demand literature i…
Optimal congestion control strategies for near-capacity urban metros: informing intervention via fundamental diagrams
Anupriya, Daniel J. Graham, Prateek Bansal +2
Congestion; operational delays due to a vicious circle of passenger-congestion and train-queuing; is an escalating problem for metro systems because it has negative consequences fr…