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Discrete Choice Models

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Showing 76–100 of 104 papers

TitleStatusHype
Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods—0
Temporal-Difference estimation of dynamic discrete choice models—0
The geometry of consumer preference aggregation—0
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks—0
The Refined Assortment Optimization Problem—0
The Relevance of Item-Co-Exposure For Exposure Bias Mitigation—0
The unreasonable effectiveness of optimal transport in economics—0
The Use of Binary Choice Forests to Model and Estimate Discrete Choices—0
Transformer Choice Net: A Transformer Neural Network for Choice Prediction—0
Two Level Nested and Sequential Logit—0
Universal Inference for Incomplete Discrete Choice Models—0
Deep Neural Networks for Choice Analysis: Extracting Complete Economic Information for Interpretation—0
Weak Identification in Discrete Choice Models—0
Yogurts Choose Consumers? Estimation of Random-Utility Models via Two-Sided Matching—0
A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health—0
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models—0
A Data Fusion Approach for Ride-sourcing Demand Estimation: A Discrete Choice Model with Sampling and Endogeneity Corrections—0
A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University—0
A Feedback Control Framework for Incentivised Suburban Parking Utilisation and Urban Core Traffic Relief—0
A Neural Network Based Choice Model for Assortment Optimization—0
A Note on "A survey of preference estimation with unobserved choice set heterogeneity" by Gregory S. Crawford, Rachel Griffith, and Alessandro Iaria—0
Approximating Choice Data by Discrete Choice Models—0
A Recursive Partitioning Approach for Dynamic Discrete Choice Modeling in High Dimensional Settings—0
Attitudes and Latent Class Choice Models using Machine learning—0
A tutorial on recursive models for analyzing and predicting path choice behavior—0
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