Machine learning advances for time series forecasting RP Masini, MC Medeiros, EF Mendes Journal of economic surveys 37 (1), 76-111, 2023 | 254 | 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 | 186* | 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 | 27 | 2022 |
A flexible particle Markov chain Monte Carlo method EF Mendes, CK Carter, D Gunawan, R Kohn Statistics and Computing, 2020 | 16* | 2020 |
On convergence rates of mixtures of polynomial experts EF Mendes, W Jiang Neural computation 24 (11), 3025-3051, 2012 | 16 | 2012 |
Adaptive LASSO estimation for ARDL models with GARCH innovations MC Medeiros, EF Mendes Econometric Reviews 36 (6-9), 622-637, 2017 | 15 | 2017 |
Testing for symmetry and conditional symmetry using asymmetric kernels M Fernandes, EF Mendes, O Scaillet Annals of the Institute of Statistical Mathematics 67, 649-671, 2015 | 11 | 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 | 3 | 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 |
Detecção de anomalias frequentes no transporte rodoviário urbano AB Cruz, J Ferreira, D Carvalho, E Mendes, E Pacitti, R Coutinho, F Porto, ... Anais do XXXIII Simpósio Brasileiro de Banco de Dados, 271-276, 2018 | 2 | 2018 |
Mining jams into pollution: how Waze data helps estimating air pollution in large cities JLM Carabetta | 1 | 2019 |
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 for high-dimensional linear processes with dependent innovations EF Mendes, F Lopes arXiv preprint arXiv:2307.12395, 2023 | | 2023 |