| Interlocking directorates in Irish companies using a latent space model for bipartite networks N Friel, R Rastelli, J Wyse, AE Raftery Proceedings of the National Academy of Sciences 113 (24), 6629-6634, 2016 | 106 | 2016 |
| Properties of latent variable network models R Rastelli, N Friel, AE Raftery Network Science 4 (4), 407-432, 2016 | 74 | 2016 |
| Choosing the number of clusters in a finite mixture model using an exact integrated completed likelihood criterion M Bertoletti, N Friel, R Rastelli Metron 73, 177-199, 2015 | 64 | 2015 |
| Optimal Bayesian estimators for latent variable cluster models R Rastelli, N Friel Statistics and Computing 28, 1169-1186, 2018 | 47 | 2018 |
| Choosing the number of groups in a latent stochastic blockmodel for dynamic networks R Rastelli, P Latouche, N Friel Network Science 6 (4), 469-493, 2018 | 22 | 2018 |
| Computationally efficient inference for latent position network models R Rastelli, F Maire, N Friel arXiv preprint arXiv:1804.02274, 2018 | 20 | 2018 |
| Measuring systemic risk and contagion in the European financial network L Tafakori, A Pourkhanali, R Rastelli Empirical economics 63 (1), 345-389, 2022 | 18 | 2022 |
| Continuous latent position models for instantaneous interactions R Rastelli, M Corneli Network Science 11 (4), 560-588, 2023 | 14 | 2023 |
| A stochastic block model for interaction lengths R Rastelli, M Fop Advances in Data Analysis and Classification 14 (2), 485-512, 2020 | 12 | 2020 |
| Exact integrated completed likelihood maximisation in a stochastic block transition model for dynamic networks R Rastelli Journal de la société française de statistique 160 (1), 35-56, 2019 | 9 | 2019 |
| The sparse latent position model for nonnegative weighted networks R Rastelli arXiv preprint arXiv:1808.09262, 2018 | 8 | 2018 |
| A model-based approach to assess epidemic risk H Dolan, R Rastelli Statistics in biosciences, 1-33, 2021 | 5 | 2021 |
| A dynamic network model to measure exposure concentration in the Austrian interbank market J Hledik, R Rastelli Statistical Methods & Applications 32 (5), 1695-1722, 2023 | 3 | 2023 |
| Latent position network models H Kaur, R Rastelli, N Friel, AE Raftery arXiv preprint arXiv:2304.02979, 2023 | 3 | 2023 |
| Choosing the number of components in a finite mixture model using an exact Integrated Completed Likelihood criteria M Bertoletti, N Friel, R Rastelli arXiv preprint arXiv:1411.4257, 2014 | 2 | 2014 |
| A latent space model for multivariate count data time series analysis H Kaur, R Rastelli arXiv preprint arXiv:2408.13162, 2024 | 1 | 2024 |
| A dynamic stochastic blockmodel for interaction lengths R Rastelli, M Fop arXiv preprint arXiv:1901.09828, 2019 | 1 | 2019 |
| A dynamic network model to measure exposure diversification in the Austrian interbank market J Hledik, R Rastelli arXiv preprint arXiv:1804.01367, 2018 | 1 | 2018 |
| A dynamic latent space time series model to assess the spread of mumps in England H Kaur, R Rastelli arXiv preprint arXiv:2411.07749, 2024 | | 2024 |
| GLAMLE: inference for multiview network data in the presence of latent variables, with an application to commodities trading C Jiang, D La Vecchia, R Rastelli Econometrics and Statistics, 2024 | | 2024 |
Nial FrielProfessor of Statistics, University College Dublin, COSTNET CA15109Zweryfikowany adres z ucd.ie