Lecture
Latent variables in choice models: Optima case study
Related lectures (31)
Understanding Preference Elicitation
Explores preference elicitation, latent variables, and the impact of external events on decision-making.
Choice models with latent variables: Modeling latent conceptsMOOC: Selected Topics on Discrete Choice
Explores choice models with latent variables and their estimation process based on likelihood integration.
Discrete Choice Analysis
Explores the integration of machine learning into discrete choice models, emphasizing the importance of theory constraints and hybrid modeling approaches.
Causal Discovery: Latent Variable Models
Explores causal discovery using latent variable models, emphasizing the challenges and solutions in inferring causal relationships from non-Gaussian data.
Choice models with latent variables: Modeling latent conceptsMOOC: Selected Topics on Discrete Choice
Explores choice models with latent variables, including indirect measurements and psychometric indicators.
Factor Models: Latent Variables and Asset Pricing
Covers Factor Models, including PCA, asset pricing, factor investing, GMM, and Fama-McBeth estimation.
Prediction TestsMOOC: Introduction to Discrete Choice Models
Discusses predicting future behavior, identifying outliers, and improving model specification.
Social Influence and Choice
Explores social influence, democracy, individual autonomy, equality, and decision-making models.
Knowledge Tracing: Student Learning and Latent Variables
Explores Bayesian Knowledge Tracing and latent variables for tracing student knowledge and making predictions.
Mixture Models: Simulation-based Estimation
Explores mixture models, including discrete and continuous mixtures, and their application in capturing taste heterogeneity in populations.