| Basketball teams as strategic networks JH Fewell, D Armbruster, J Ingraham, A Petersen, JS Waters PloS one 7 (11), e47445, 2012 | 259 | 2012 |
| Fréchet regression for random objects with Euclidean predictors A Petersen, HG Müller The Annals of Statistics 47 (2), 691-719, 2019 | 196 | 2019 |
| Functional data analysis for density functions by transformation to a Hilbert space A Petersen, HG Müller | 191 | 2016 |
| Blood pressure variability predicts poor in-hospital outcome in spontaneous intracerebral hemorrhage AA Divani, XI Liu, M Di Napoli, S Lattanzi, W Ziai, ML James, A Jafarli, ... Stroke 50 (8), 2023-2029, 2019 | 107 | 2019 |
| Modeling probability density functions as data objects A Petersen, C Zhang, P Kokoszka Econometrics and Statistics 21, 159-178, 2022 | 56 | 2022 |
| Quantifying infinite-dimensional data: Functional data analysis in action K Chen, X Zhang, A Petersen, HG Müller Statistics in Biosciences 9, 582-604, 2017 | 52 | 2017 |
| Partial separability and functional graphical models for multivariate Gaussian processes J Zapata, SY Oh, A Petersen Biometrika 109 (3), 665-681, 2022 | 48 | 2022 |
| Forecasting of density functions with an application to cross-sectional and intraday returns P Kokoszka, H Miao, A Petersen, HL Shang International Journal of Forecasting 35 (4), 1304-1317, 2019 | 48 | 2019 |
| Wasserstein autoregressive models for density time series C Zhang, P Kokoszka, A Petersen Journal of Time Series Analysis 43 (1), 30-52, 2022 | 46 | 2022 |
| Glucodensities: A new representation of glucose profiles using distributional data analysis M Matabuena, A Petersen, JC Vidal, F Gude Statistical methods in medical research 30 (6), 1445-1464, 2021 | 43 | 2021 |
| Wasserstein covariance for multiple random densities A Petersen, HG Müller Biometrika 106 (2), 339-351, 2019 | 37 | 2019 |
| Blood pressure variability: a new predicting factor for clinical outcomes of intracerebral hemorrhage S Andalib, S Lattanzi, M Di Napoli, A Petersen, J Biller, T Kulik, E Macri, ... Journal of Stroke and Cerebrovascular Diseases 29 (12), 105340, 2020 | 33 | 2020 |
| Wasserstein -tests and confidence bands for the Fréchet regression of density response curves A Petersen, X Liu, AA Divani | 32 | 2021 |
| Fréchet integration and adaptive metric selection for interpretable covariances of multivariate functional data A Petersen, HG Müller Biometrika 103 (1), 103-120, 2016 | 25 | 2016 |
| Distributional data analysis of accelerometer data from the NHANES database using nonparametric survey regression models M Matabuena, A Petersen Journal of the Royal Statistical Society Series C: Applied Statistics 72 (2 …, 2023 | 24 | 2023 |
| The magnitude of blood pressure reduction predicts poor in-hospital outcome in acute intracerebral hemorrhage AA Divani, X Liu, A Petersen, S Lattanzi, CS Anderson, W Ziai, MT Torbey, ... Neurocritical care 33, 389-398, 2020 | 21 | 2020 |
| Fréchet estimation of time-varying covariance matrices from sparse data, with application to the regional co-evolution of myelination in the developing brain A Petersen, S Deoni, HG Müller The Annals of Applied Statistics 13 (1), 393-419, 2019 | 19 | 2019 |
| Distributionally robust formulation and model selection for the graphical lasso P Cisneros-Velarde, A Petersen, SY Oh International Conference on Artificial Intelligence and Statistics, 756-765, 2020 | 17 | 2020 |
| Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules A Oikonomou, P Salazar, Y Zhang, DM Hwang, A Petersen, AA Dmytriw, ... Scientific reports 9 (1), 6009, 2019 | 17 | 2019 |
| Exploration of multiparameter hematoma 3D image analysis for predicting outcome after intracerebral hemorrhage P Salazar, M Di Napoli, M Jafari, A Jafarli, W Ziai, A Petersen, SA Mayer, ... Neurocritical care 32, 539-549, 2020 | 15 | 2020 |
