Publications

Export 0 results:
[ Author(Asc)] Title Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
A
N. Atanov, Baranov, V., Budagov, J., Cervelli, F., Colao, F., Cordelli, M., Corradi, G., Dané, E., Davydov, Y. I., Di Falco, S., Diociaiuti, E., Donati, S., Donghia, R., Echenard, B., Flood, K., Giovannella, S., Glagolev, V., Grancagnolo, F., Happacher, F., Hitlin, D. G., Martini, M., Miscetti, S., Miyashita, T., Morescalchi, L., Murat, P., Pezzullo, G., Porter, F., Raffaelli, F., Radicioni, T., Ricci, M., Saputi, A., Sarra, I., Spinella, F., Tassielli, G., Tereshchenko, V., Usubov, Z., and Zhu, R. Y., The calorimeter of the Mu2e experiment at Fermilab, Journal of Instrumentation, vol. 12, 2017.
M. Andreani and Petrella, L., Dynamic Quantile Regression Forest, SIS 2020 - 50th Conference of the Italian Statistical Society, vol. Book of Short Papers SIS 2020. Pearson, 2020.
M. Andreani, Candila, V., and Petrella, L., Quantile Regression Forest with mixed-frequency data, vol. Book of Short Papers SIS 2021. Pearson, 2021.
M. Andreani, Candila, V., Morelli, G., and Petrella, L., Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach, Risks, vol. 9, p. 144, 2021.
M. Andreani, Candila, V., and Petrella, L., Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data, Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham, 2022.
Zircon - This is a contributing Drupal Theme
Design by WeebPal.