Results 11 to 20 of about 1,913,123 (347)
Discrete Choice Models with Random Parameters in R: The Rchoice Package
Journal of Statistical Software, 2016 Rchoice is a package in R for estimating models with individual heterogeneity for both cross-sectional and panel (longitudinal) data. In particular, the package allows binary, ordinal and count response, as well as continuous and discrete covariates ...
Mauricio Sarrias
doaj +2 more sources
Duality in Dynamic Discrete Choice Models [PDF]
SSRN Electronic Journal, 2015 Using results from convex analysis, we investigate a novel approach to identification and estimation of discrete choice models which we call the "Mass Transport Approach" (MTA). We show that the conditional choice probabilities and the choice-specific payoffs in these models are related in the sense of conjugate duality, and that the identification ...
Chiong, Khai X. +2 more
openaire +10 more sources
Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms [PDF]
Journal of Choice Modeling, 2020 The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the ...
Gael Lederrey +3 more
semanticscholar +1 more source
Assisted specification of discrete choice models
Journal of Choice Modeling, 2021 Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger and larger datasets, as the number of possible specifications exponentially grows with the number of ...
Nicola Ortelli +4 more
semanticscholar +1 more source
Integrating advanced discrete choice models in mixed integer linear optimization
, 2021 The integration of customer behavioral models in operations research (OR) is appealing to operators and policy makers (the supply) because it provides a better understanding of the preferences of customers (the demand) while planning for their systems ...
M. Bierlaire, M. Pacheco
semanticscholar +1 more source
Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments. [PDF]
Int Econ Rev (Philadelphia), 2015 We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of ...
Eisenhauer P, Heckman JJ, Mosso S.
europepmc +2 more sources
Enhancing discrete choice models with representation learning
Transportation Research Part B: Methodological, 2020 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 ...
Brian Sifringer +2 more
semanticscholar +1 more source
Identifying the discount factor in dynamic discrete choice models [PDF]
Quantitative Economics, 2018 Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences.
Jaap H. Abbring, Oystein Daljord
semanticscholar +1 more source
Developing wine tourism experiences. A discrete choice analysis using best-worst scaling data
Wine Economics and Policy, 2022 The aim of this research is to aid winery managers in bundling a plethora of different service features to meet the wine tourists’ expectations. A discrete choice model using best-worst scaling (BWS) data is estimated to obtain the relative importance of
Giacomo Del Chiappa +2 more
doaj +1 more source
Identifying dynamic discrete choice models off short panels
Journal of Econometrics, 2020 This paper analyzes the identification of flow payoffs and counterfactual choice probabilities (CCPs) in single-agent dynamic discrete choice models. We develop new results on non-stationary models where the time horizon for the agent extends beyond the ...
Peter Arcidiacono Robert A. Miller
semanticscholar +1 more source