Object-fine choice models for long-term decisions: which level of granularity is necessary? A review of literature VAN EGGERMOND Michael A.B.* , ERATH Alexander* , and AXHAUSEN Kay W.** *

Source URL: www.strc.ch

• Transportation planning
• Choice modelling
• Simulation
• Statistics
• Discrete choice
• Economy
• Trip distribution
• Mode choice
• UrbanSim
• Mixed logit
• Accessibility
• Multinomial logistic regression

Accounting for similarities in destination choice modelling: A concept Nadine Schüssler Kay W. Axhausen STRC 2009

Source URL: www.strc.ch

• Choice modelling
• Transportation planning
• Statistical models
• Decision theory
• Discrete choice
• Mode choice
• Mixed logit
• Choice set
• Trip distribution
• Scientific modelling
• Choice
• Decision-making

Simulation of Pedestrian Behaviour using a Discrete Choice Model Calibrated on Actual Motion Data Gianluca Antonini, Michel Bierlaire and Mats Weber Signal Processing Institute Swiss Federal Institute of Technology Lausa

Source URL: www.strc.ch

• Statistics
• Statistical models
• Mathematical analysis
• Choice modelling
• Regression analysis
• Transportation planning
• Discrete choice
• Mathematics
• Logit
• Traffic simulation
• Trip distribution
• Economic model

Discrete mixtures of GEV models Stephane Hess, Imperial College London & RAND Europe Michel Bierlaire, EPFL John W. Polak, Imperial College London Conference paper STRC 2005

Source URL: www.strc.ch

• Statistical models
• Regression analysis
• Choice modelling
• Discrete choice
• Mode choice
• Mixed logit
• Probability distribution
• Multinomial logistic regression
• Logistic regression
• Likelihood function
• Mixture model
• Gibbs sampling

Company decisions on choice of location Case study: St. Gallen region Balz R. Bodenmann, IVT, ETH Zürich Conference paper STRC 2007

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• Migration
• Logit

Estimation of discrete choice models: extending BIOGEME Michel Bierlaire Mamy Fetiarison STRC 2009

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• Statistics
• Statistical models
• Regression analysis
• Choice modelling
• Discrete choice
• Iterator
• Logistic regression
• Logit
• Binomial regression
• Mixed logit

Start: Haugesund, Rogaland, Norway End: Trondheim, Sør-Trøndelag, Norway Total Distance: Miles Estimated Total Time: 47 hours, 31 minutes Source: http://www.mappoint.msn.com (Jan 31, 2005)

Source URL: www.strc.ch

• Statistical models
• Choice modelling
• Single-equation methods
• Regression analysis
• Discrete choice
• Mixed logit
• Multinomial logistic regression
• Shortest path problem
• Logit
• Probit
• Logistic regression
• Pairwise comparison

SOCIOLOGICAL Allison / LOGIT AND METHODS PROBIT&COEFFICIENTS RESEARCH

Source URL: statisticalhorizons.com

Swiss second-home owners’ intention to move to their dwelling: an integrated ordered logit model with latent variable. Igor Sarman, University of Lugano (USI – Switzerland) Conference paper STRC 2014

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• Statistics
• Statistical models
• Academia
• Psychometrics
• Social research
• Regression analysis
• Categorical data
• Discrete choice
• Choice modelling
• Latent variable
• Observable variable
• Logistic regression

Model 1 (Judge Clustering, Common Space Scores): . **(1-a) logit, if fe_dec==1, clm_rel<99, and clustered at Judge_ID . logit FE_OUTCM fe_reg fe_pred fe_puel fe_pued fe_mtg fe_exp fe_zon fe_pris fe_emp fe_crim fe_exm cl

Source URL: courseweb.stthomas.edu