Combining Predictive Densities Using Bayesian Filtering with Applications to US Economic Data

Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data

Bayesian Predictive Profiles With Applications to Retail Transaction Data

Massive transaction data sets are recorded in a routine manner in telecommunications, retail commerce, and Web site management. In this paper we address the problem of inferring predictive individual profiles from such historical transaction data. We describe a generative mixture model for count data and use an an approximate Bayesian estimation framework that effectively combines an individual...

Time-varying Combinations of Predictive Densities using Nonlinear Filtering

We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced with a particular focus on weight dynamics driven by the past performance of the predictive densities and the use of learning mechanisms. In the propos...

Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities

In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model is to estimate its future predictive capability by estimating expected utilities. Instead of just making a point estimate, it is important to obtain the distribution of the expected utility estimate because it describ...

Using stacking to average Bayesian predictive distributions Using stacking to average Bayesian predictive distributions

Abstract The widely recommended procedure of Bayesian model averaging is flawed in the M-open setting in which the true data-generating process is not one of the candidate models being fit. We take the idea of stacking from the point estimation literature and generalize to the combination of predictive distributions, extending the utility function to any proper scoring rule, using Pareto smooth...