Papers in Refereed journals:

17. Iacopini, M., Poon, A., Rossini, L. and Zhu, D. (2023) - Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP.   Journal of Economic Dynamics and Control, 157, 104757

 

16. Iacopini, M., Ravazzolo, F. and Rossini, L. (2023) - Proper Scoring Rules for evaluating density forecasting with asymmetric loss function. Journal of Business and Economic Statistics, 41:2, 482-486 Matlab Code 

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15. Gianfreda, A., Ravazzolo, F. and Rossini, L. (2023) - Large Time-Varying Volatility Models for Electricity Prices. Oxford Bulletin of Economics and Statistics, 85:3, 545-573

 

14. Foroni, C., Ravazzolo, F and Rossini, L. (2023) - Are low frequency macroeconomic variables important for high frequency electricity prices? Economic Modelling, 120, 106160

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13. Huber, F. and Rossini, L. (2022) - Inference in Bayesian Additive Vector Autoregressive Tree Models. Annals of Applied Statistics. 16:1, 104-123

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12. Durante, F., Gianfreda, A., Ravazzolo, F. and Rossini, L. (2022) - A Multivariate Dependence Analysis for Electricity Prices, Demand and Renewable Energy Sources. Information Sciences, 590, 74-89

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11. Dalla Valle,L., Leisen, F., Rossini, L. and Zhu, W. (2021) - A Pòlya-Gamma Sampler for a Generalized Logistic Regression. Journal of Statistical Computation and Simulation, 91:14, 2899-2916 - R Code

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10. Bassetti, F., Casarin, R. and Rossini, L. (2020) - Hierarchical Species Sampling Models. Bayesian Analysis, 15:3, 809-838

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9. Gianfreda, A., Ravazzolo, F. and Rossini, L. (2020) - Comparing the Forecasting Performance of Linear Models for Electricity Prices with High RES Penetration. International Journal of Forecasting, 36:3, 974-986

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8. Leisen, F., Rossini, L. and Villa, C. (2020) -  Loss-based approach to two-piece location-scale distributions with applications to dependent data. Statistical Methods & Applications, 29, 309-333

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7. Dalla Valle, L., Leisen, F., Rossini, L. and Zhu, W. (2020) - Bayesian Analysis of Immigration in Europe with Generalized Logistic Regression. Journal of Applied Statistics, 47:3, 424-438  -  R Code

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6. Billio, M., Casarin, R. and Rossini, L. (2019) - Bayesian nonparametric sparse VAR models. Journal of Econometrics, 212, 97-115

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5. Bohte, R. and Rossini, L. (2019) - Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models. Journal of Risk and Financial Management, 12:3, 150

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4. Leisen, F., Mena, R.H., Palma, F. and Rossini, L. (2019) - On a flexible construction of a negative binomial model. Statistics & Probability Letters, 152, 1-8

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3. Dalla Valle, L., Leisen, F. and Rossini, L. (2018) - Bayesian nonparametric conditional copula estimation of Twin data. Journal of the Royal Statistical Society (Series C), 67:3, 523-548 - Matlab Code

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2. Leisen, F., Rossini, L. and Villa, C. (2018) - Objective Bayesian Analysis of the Yule-Simon Distribution with Applications. Computational Statistics, 33:1, 99-126

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1. Leisen, F., Rossini, L. and Villa, C. (2017) - A note on the posterior inference for the Yule–Simon distribution. Journal of Statistical Computation and Simulation, 87:6, 1179-1188

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