| A unifying approach for doubly-robust ℓ1 regularized estimation of causal contrasts E Smucler, A Rotnitzky, JM Robins arXiv preprint arXiv:1904.03737, 2019 | 103 | 2019 |
| Robust and sparse estimators for linear regression models E Smucler, VJ Yohai Computational Statistics & Data Analysis 111, 116-130, 2017 | 102 | 2017 |
| Efficient adjustment sets for population average causal treatment effect estimation in graphical models A Rotnitzky, E Smucler Journal of Machine Learning Research 21 (188), 1-86, 2020 | 93* | 2020 |
| Characterization of parameters with a mixed bias property A Rotnitzky, E Smucler, JM Robins Biometrika 108 (1), 231-238, 2021 | 81 | 2021 |
| Robust elastic net estimators for variable selection and identification of proteomic biomarkers GV Cohen Freue, D Kepplinger, M Salibián-Barrera, E Smucler Annals of Applied Statistics 13 (4), 2065-2090, 2019 | 39* | 2019 |
| Forecasting multiple time series with one-sided dynamic principal components D Peña, E Smucler, VJ Yohai Journal of the American Statistical Association, 2019 | 32 | 2019 |
| Efficient adjustment sets in causal graphical models with hidden variables E Smucler, F Sapienza, A Rotnitzky Biometrika 109 (1), 49-65, 2022 | 27 | 2022 |
| Split regularized regression AA Christidis, L Lakshmanan, E Smucler, R Zamar Technometrics 62 (3), 330-338, 2020 | 23* | 2020 |
| Uncovering differential equations from data with hidden variables A Somacal, Y Barrera, L Boechi, M Jonckheere, V Lefieux, D Picard, ... Physical Review E 105 (5), 054209, 2022 | 19 | 2022 |
| Intergenerational transmission of maternal care deficiency and offspring development delay induced by perinatal protein malnutrition O Gianatiempo, SV Sonzogni, EA Fesser, LM Belluscio, E Smucler, ... Nutritional Neuroscience 23 (5), 387-397, 2020 | 19 | 2020 |
| Validation strategies for satellite-based soil moisture products over Argentine Pampas F Grings, CA Bruscantini, E Smucler, F Carballo, ME Dillon, EA Collini, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2015 | 19 | 2015 |
| Asymptotic theory for maximum likelihood estimates in reduced-rank multivariate generalized linear models E Bura, S Duarte, L Forzani, E Smucler, M Sued Statistics 52 (5), 1005-1024, 2018 | 11 | 2018 |
| Sufficient dimension reduction and prediction in regression: Asymptotic results L Forzani, D Rodriguez, E Smucler, M Sued Journal of Multivariate Analysis 171, 339-349, 2019 | 9 | 2019 |
| Asymptotics for redescending M-estimators in linear models with increasing dimension E Smucler Statistica Sinica 29 (2), 1065-1081, 2019 | 8* | 2019 |
| A note on efficient minimum cost adjustment sets in causal graphical models A Rotnitzky, E Smucler Journal of Causal Inference, 2022 | 6* | 2022 |
| Estimadores robustos para el modelo de regresión lineal con datos de alta dimensión E Smucler | 6 | 2016 |
| Highly robust and highly finite sample efficient estimators for the linear model E Smucler, VJ Yohai Modern Nonparametric, Robust and Multivariate Methods: Festschrift in Honour …, 2015 | 6 | 2015 |
| Sparse estimation of dynamic principal components for forecasting high-dimensional time series D Peña, E Smucler, VJ Yohai International Journal of Forecasting 37 (4), 1498-1508, 2021 | 4 | 2021 |
| gdpc: an R package for generalized dynamic principal components D Peña, E Smucler, VJ Yohai Journal of Statistical Software 92, 1-23, 2020 | 3 | 2020 |
| Consistency of generalized dynamic principal components in dynamic factor models E Smucler Statistics & Probability Letters 154, 108536, 2019 | 3 | 2019 |
Andrea RotnitzkyProfessor, University of Washington, Seattle在 uw.edu 的电子邮件经过验证
