Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

Bayesian Estimation of Dynamic Discrete Choice Models

We propose a new estimator for dynamic programming discrete choice models. Our estimation method combines the Dynamic Programming algorithm with a Bayesian Markov Chain Monte Carlo algorithm into one single Markov Chain algorithm that solves the dynamic programming problem and estimates the parameters at the same time. Our key innovation is that during each solution-estimation iteration both th...

Learning High-Dimensional Concave Utility Functions for Discrete Choice Models

The discrete choice model explains and predicts the behavior of a consumer who chooses one item to purchase from among a set of alternatives. The consumer is assumed to assign a utility to each item based on its features, and to choose an item with probability proportional to its utility. We consider the high-dimensional setting where the number of item features is large. It is important in thi...

Random Utility-Based Discrete Choice Models for Travel Demand Analysis

Automatic relevance determination based hierarchical Bayesian MEG inversion in practice

In recent simulation studies, a hierarchical Variational Bayesian (VB) method, which can be seen as a generalisation of the traditional minimum-norm estimate (MNE), was introduced for reconstructing distributed MEG sources. Here, we studied how nonlinearities in the estimation process and hyperparameter selection affect the inverse solutions, the feasibility of a full Bayesian treatment of the ...

Bayesian sample size Determination Using a Scaled Exponential Utility Function According to Numerical Method

‎In this paper we propose a utility function and obtain the Bayese stimate and the optimum sample size under this utility function‎. ‎This utility function is designed especially to obtain the Bayes estimate when the posterior follows a gamma distribution‎. ‎We consider a Normal with known mean‎, ‎a Pareto‎, ‎an Exponential and a Poisson distribution for an optimum sample size under the propose...