| Dynamic model-based clustering for spatio-temporal data L Paci, F Finazzi Statistics and Computing 28 (2), 359-374, 2018 | 24 | 2018 |
| Spatio-temporal modeling for real-time ozone forecasting L Paci, AE Gelfand, DM Holland Spatial statistics 4, 79-93, 2013 | 20 | 2013 |
| Analysis of residential property sales using space–time point patterns L Paci, MA Beamonte, AE Gelfand, P Gargallo, M Salvador Spatial Statistics 21, 149-165, 2017 | 19 | 2017 |
| Quantifying personal exposure to air pollution from smartphone‐based location data F Finazzi, L Paci Biometrics 75 (4), 1356-1366, 2019 | 17 | 2019 |
| Space-time modeling for post-fire vegetation recovery L Paci, AE Gelfand, MA Beamonte, M Rodrigues, F Pérez-Cabello Stochastic Environmental Research and Risk Assessment 31, 171-183, 2017 | 15 | 2017 |
| Structural learning of contemporaneous dependencies in graphical VAR models L Paci, G Consonni Computational Statistics & Data Analysis 144, 106880, 2020 | 14 | 2020 |
| Gaussian graphical modeling for spectrometric data analysis L Codazzi, A Colombi, M Gianella, R Argiento, L Paci, A Pini Computational Statistics & Data Analysis 174, 107416, 2022 | 12 | 2022 |
| Score-driven modeling of spatio-temporal data F Gasperoni, A Luati, L Paci, E D’Innocenzo Journal of the American Statistical Association 118 (542), 1066-1077, 2023 | 11 | 2023 |
| Spatial hedonic modelling adjusted for preferential sampling L Paci, AE Gelfand, MA Beamonte, P Gargallo, M Salvador Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2020 | 8 | 2020 |
| Kernel-based estimation of individual location densities from smartphone data F Finazzi, L Paci Statistical Modelling 20 (6), 617-633, 2019 | 5 | 2019 |
| Quantifying uncertainty for temperature maps derived from computer models L Paci, AE Gelfand, D Cocchi Spatial Statistics 12, 96-108, 2015 | 5 | 2015 |
| A practical approach for assessing the effect of grouping in hierarchical spatio-temporal models F Bruno, D Cocchi, L Paci AStA Advances in Statistical Analysis 97, 93-108, 2013 | 5 | 2013 |
| Connecting statistical brains A Canale, D Durante, L Paci, B Scarpa Significance 15 (1), 38-40, 2018 | 4 | 2018 |
| Learning block structured graphs in Gaussian graphical models A Colombi, R Argiento, L Paci, A Pini Journal of Computational and Graphical Statistics 33 (1), 152-165, 2024 | 3 | 2024 |
| Spatiotemporal model for short-term predictions of air pollution data F Bruno, L Paci The Contribution of Young Researchers to Bayesian Statistics: Proceedings of …, 2013 | 3 | 2013 |
| Studies in Neural Data Science A Canale, D Durante, L Paci, B Scarpa SPRINGER PROCEEDINGS IN MATHEMATICS & STATISTICS 257, 2018 | 2 | 2018 |
| Model-based clustering of categorical data based on the Hamming distance R Argiento, E Filippi-Mazzola, L Paci Journal of the American Statistical Association, 1-23, 2024 | 1 | 2024 |
| Multivariate Stochastic Downscaling for Semicontinuous Data L Paci, C Trivisano, D Cocchi Classification,(Big) Data Analysis and Statistical Learning, 107-115, 2018 | | 2018 |
| Dynamic data fusion approach for air quality assessment L Paci, G Bonafè, C Trivisano Air Pollution Modeling and its Application XXIV, 629-633, 2016 | | 2016 |
alan e gelfandProfessor of Statistical Science Duke UniversityVerified email at stat.duke.edu
