174 citations · 224 across the 4 of their papers we have counts for
4 papers
Scalable Rejection Sampling for Bayesian Hierarchical Models
Michael Braun, Paul Damien
Bayesian hierarchical modeling is a popular approach to capturing unobserved heterogeneity across individual units. However, standard estimation methods such as Markov chain Monte…
Generalized Direct Sampling for Hierarchical Bayesian Models
Michael Braun, Paul Damien
We develop a new method to sample from posterior distributions in hierarchical models without using Markov chain Monte Carlo. This method, which is a variant of importance sampling…
Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes
Michael Braun, André Bonfrer
Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions…
Variational inference for large-scale models of discrete choice
Michael Braun, Jon McAuliffe
Discrete choice models are commonly used by applied statisticians in numerous fields, such as marketing, economics, finance, and operations research. When agents in discrete choice…