95 citations · 168 across the 22 of their papers we have counts for
24 papers
A Conversation with Mike West
Hedibert F. Lopes, Filippo Ascolani
Mike West is currently the Arts & Sciences Distinguished Professor Emeritus of Statistics and Decision Sciences at Duke University. Mike's research in Bayesian analysis spans multi…
Generative Bayesian Hyperparameter Tuning
Hedibert Lopes, Nick Polson, Vadim Sokolov
\noindent Hyper-parameter selection is a central practical problem in modern machine learning, governing regularization strength, model capacity, and robustness choices. Cross-vali…
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…
What events matter for exchange rate volatility ?
Igor Martins, Hedibert Freitas Lopes
This paper expands on stochastic volatility models by proposing a data-driven method to select the macroeconomic events most likely to impact volatility. The paper identifies and q…
Stochastic volatility models with skewness selection
Igor Ferreira Batista Martins, Hedibert Freitas Lopes
This paper expands traditional stochastic volatility models by allowing for time-varying skewness without imposing it. While dynamic asymmetry may capture the likely direction of f…