| Machine learning advances for time series forecasting RP Masini, MC Medeiros, EF Mendes Journal of economic surveys 37 (1), 76-111, 2023 | 389 | 2023 |
| ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors MC Medeiros, EF Mendes Journal of Econometrics 191 (1), 255-271, 2016 | 196* | 2016 |
| Regularized estimation of high‐dimensional vector autoregressions with weakly dependent innovations RP Masini, MC Medeiros, EF Mendes Journal of Time Series Analysis 43 (4), 532-557, 2022 | 30 | 2022 |
| A flexible particle Markov chain Monte Carlo method EF Mendes, CK Carter, D Gunawan, R Kohn Statistics and Computing, 2020 | 17* | 2020 |
| On convergence rates of mixtures of polynomial experts EF Mendes, W Jiang Neural computation 24 (11), 3025-3051, 2012 | 17 | 2012 |
| Adaptive LASSO estimation for ARDL models with GARCH innovations MC Medeiros, EF Mendes Econometric Reviews 36 (6-9), 622-637, 2017 | 16 | 2017 |
| Testing for symmetry and conditional symmetry using asymmetric kernels M Fernandes, EF Mendes, O Scaillet Annals of the Institute of Statistical Mathematics 67 (4), 649-671, 2015 | 12 | 2015 |
| Some new approaches to forecasting the price of electricity: a study of californian market EF Mendes, L Oxley, M Reale Department of Economics, 2008 | 8 | 2008 |
| An extended space approach for particle Markov chain Monte Carlo methods CK Carter, EF Mendes, R Kohn arXiv preprint arXiv:1406.5795, 2014 | 7 | 2014 |
| Model selection consistency for cointegrating regressions EF Mendes arXiv preprint arXiv:1104.5667, 2011 | 6 | 2011 |
| A note on nonlinear cointegration, misspecification, and bimodality MC Medeiros, E Mendes, L Oxley Econometric Reviews 33 (7), 713-731, 2014 | 5* | 2014 |
| Cointegrating smooth transition regressions with a stationary transition variable M Medeiros, E MENDES, L Oxley Working paper, Pontifical Catholic University of Rio de Janeiro, 2011 | 5 | 2011 |
| Estimation and asymptotic theory for a new class of mixture models EF Mendes, A Veiga, MC Medeiros Texto para discussão, 2007 | 5 | 2007 |
| Markov interacting importance samplers EF Mendes, M Scharth, R Kohn arXiv preprint arXiv:1502.07039, 2015 | 4 | 2015 |
| Penalized estimation of semi-parametric additive time-series models M Medeiros, E Mendes Essays in nonlinear time series econometrics. Oxford University Press, 2013 | 3 | 2013 |
| Mining jams into pollution: how Waze data helps estimating air pollution in large cities JLM Carabetta | 2 | 2019 |
| Detecção de anomalias frequentes no transporte rodoviário urbano AB Cruz, J Ferreira, D Carvalho, E Mendes, E Pacitti, R Coutinho, F Porto, ... Simpósio Brasileiro de Banco de Dados (SBBD), 271-276, 2018 | 2 | 2018 |
| Long memory or shifting means? A new approach and application to realised volatility W Rea, L Oxley, M Reale, E Mendes Department of Economics and Finance, 2008 | 1 | 2008 |
| Generalized Information Criteria for Structured Sparse Models EF Mendes, GJP Pinto arXiv preprint arXiv:2309.01764, 2023 | | 2023 |
| Concentration inequalities for high-dimensional linear processes with dependent innovations EF Mendes, F Lopes arXiv preprint arXiv:2307.12395, 2023 | | 2023 |
Marcelo C. MedeirosProfessor, Department of Economics, The University of Illinois at Urbana-ChampaignEmail verificata su illinois.edu
