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PyKernelLogit: Penalised maximum likelihood estimation of Kernel Logistic Regression in Python
4 references·1 citing·22 second hop
PyKernelLogit: Penalised maximum likelihood estimation of Kernel Logistic Regression in Python (2023)PyKernelLogit: Penalised maximum likeliho…Public transport users' willingness-to-pay for a multi-county and multi-operator integrated ticket: Valuation and policy implications (2022)Public transport users' willi…Estimation of Random Utility Models in R: The mlogit Package (2020)Estimation of Random Utility …Public transport values of time (2004)Public transport values of ti…UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning (2002)UrbanSim: Modeling Urban Deve…Traveler time allocation between activities and travel: A computational graph-infused machine learning framework with bi-mode MDCEV model (2025)Traveler time allocation betw…Conditional logit analysis of qualitative choice behavior (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)Microsimulation of Urban Development and Location Choices: Design and Implementation of UrbanSim (2003)Residential Relocation and Changes in Urban Travel: Does Neighborhood-Scale Urban Form Matter? (2003)Overview of Land Use Transport Models (2004)The measurement of urban travel demand (1974)The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models (1993)Discrete Choice Methods with Simulation (2001)Generating Optimal Designs for Discrete Choice Experiments in R: The idefix Package (2020)Examining changes in parent‐reported child and adolescent mental health throughout the UK's first COVID‐19 national lockdown (2021)What’s the Appeal? Perceptions of Review Processes for Algorithmic Decisions (2022)Smart card data use in public transit: A literature review (2011)Applied Choice Analysis (2015)Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application (2019)Influence of Differentiated Tolling Strategies on Route Choice Behavior of Heterogeneous Highway Users (2025)Discrete/Continuous Models of Consumer Demand (1984)Activity-based disaggregate travel demand model system with activity schedules (2001)How derived is the demand for travel? Some conceptual and measurement considerations (2001)The demand for public transport: a practical guide (2004)Valuation of travel time (2012)Value of travel time reliability: A review of current evidence (2012)
this work references cited by second hop

References

  • 2002UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning1,216 cited
  • 2004Public transport values of time626 cited
  • 2020Estimation of Random Utility Models in R: The mlogit Package231 cited
  • 2022Public transport users' willingness-to-pay for a multi-county and multi-operator integrated ticket: Valuation and policy implications10 cited

Cited by

  • 2025Traveler time allocation between activities and travel: A computational graph-infused machine learning framework with bi-mode MDCEV model3 cited

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