95 citations · 168 across the 22 of their papers we have counts for
12 papers · 1 filter
Lower-dimensional posterior density and cluster summaries for overparameterized Bayesian models
Henrique Bolfarine, Hedibert F. Lopes, Carlos M. Carvalho
The usefulness of Bayesian models for density and cluster estimation is well established across multiple literatures. However, there is still a known tension between the use of sim…
Minnesota BART
Pedro A. Lima, Carlos M. Carvalho, Hedibert F. Lopes +1
Vector autoregression (VAR) models are widely used for forecasting and macroeconomic analysis, yet they remain limited by their reliance on a linear parameterization. Recent resear…
Sparse Bayesian factor analysis when the number of factors is unknown
Sylvia Frühwirth-Schnatter, Darjus Hosszejni, Hedibert Freitas Lopes
There has been increased research interest in the subfield of sparse Bayesian factor analysis with shrinkage priors, which achieve additional sparsity beyond the natural parsimonit…
When it counts -- Econometric identification of the basic factor model based on GLT structures
Sylvia Frühwirth-Schnatter, Darjus Hosszejni, Hedibert Freitas Lopes
Despite the popularity of factor models with sparse loading matrices, little attention has been given to formally address identifiability of these models beyond standard rotation-b…
The Illusion of the Illusion of Sparsity: An exercise in prior sensitivity
Bruno Fava, Hedibert F. Lopes
The emergence of Big Data raises the question of how to model economic relations when there is a large number of possible explanatory variables. We revisit the issue by comparing t…
Dynamic sparsity on dynamic regression models
Paloma W. Uribe, Hedibert F. Lopes
In the present work, we consider variable selection and shrinkage for the Gaussian dynamic linear regression within a Bayesian framework. In particular, we propose a novel method t…