Publications related to Multinomial probit

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Sampling of alternatives in migration aspiration models

Michel Bierlaire, Evangelos Paschalidis

The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...

2023

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Urs von Gunten

Ozonation of secondary-treated wastewater for the abatement of micropollutants requires a reliable control of ozone doses. Changes in the UV absorbance of dissolved organic matter (DOM) during ozonation allow to estimate micropollutant abatement on-line an ...

PERGAMON-ELSEVIER SCIENCE LTD2022

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models ...

INFORMS2021

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Models that are robust to aberrant choice behaviour have received limited attention in discrete choice analysis. In this paper, we analyse two robust alternatives to the multinomial probit (MNP) model. Both alternative models belong to the family of robit ...

EPFL2020

Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets

Virginie Janine Camille Lurkin, Jeffrey Newman

Network planning models, which forecast the profitability of airline schedules, support many critical decisions, including equipment purchase decisions. Network planning models include an itinerary choice model that is used to allocate air total demand in ...

Pergamon-Elsevier Science Ltd2017

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistica ...

2017

Uncovering substitution patterns in new car sales using a cross nested logit model

Michel Bierlaire, Matthieu Marie Cochon de Lapparent, Anna Fernández Antolín

In the context of sales of new cars it is important to understand and model the consumers substitution patterns as well as their price elasticity towards different types of cars. To do so we develop (i) a multinomial logit model (MNL) and (ii) a cross-nest ...

2016

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Multinomial probit

Robust discrete choice models with t-distributed kernel errors

Sampling of alternatives in migration aspiration models

Ride-sourcing fleet rebalancing with proactive and targeted pricing

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Robust discrete choice models with t-distributed kernel errors

Enhancing discrete choice models with representation learning

Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Uncovering substitution patterns in new car sales using a cross nested logit model

Graph Chatbot

Chat with Graph Search

Sampling of alternatives in migration aspiration models

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Robust discrete choice models with t-distributed kernel errors

Enhancing discrete choice models with representation learning

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Robust discrete choice models with t-distributed kernel errors

Ride-sourcing fleet rebalancing with proactive and targeted pricing

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets

Uncovering substitution patterns in new car sales using a cross nested logit model