5 papers
Scalable likelihood-based inference for limited dependent variable models
David T. Frazier, Ruben Loaiza-Maya, Didier Nibbering
Limited dependent variable models are central to empirical economics, but likelihood-based inference is infeasible when likelihoods involve high-dimensional integration over latent…
A Multinomial Probit Model for Asymmetric Choice Responses
Cash Looi, Ruben Loaiza-Maya, Didier Nibbering
Standard multinomial probit (MNP) models specify symmetric latent utility distributions, implying that choice probabilities respond symmetrically to positive and negative covariate…
Conjugating Variational Inference for Large Mixed Multinomial Logit Models and Consumer Choice
Weiben Zhang, Ruben Loaiza-Maya, Michael Stanley Smith +1
Heterogeneity in multinomial choice data is often accounted for using logit models with random coefficients. Such models are called "mixed", but they can be difficult to estimate f…
Robustifying Approximate Bayesian Computation
Chaya Weerasinghe, David T. Frazier, Ruben Loaiza-Maya +1
Approximate Bayesian computation (ABC) is one of the most popular "likelihood-free" methods. These methods have been applied in a wide range of fields by providing solutions to int…
Natural Gradient Hybrid Variational Inference with Application to Deep Mixed Models
Weiben Zhang, Michael Stanley Smith, Worapree Maneesoonthorn +1
Stochastic models with global parameters and latent variables are common, and for which variational inference (VI) is popular. However, existing methods are often either slow or in…