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ORCIDMarcelo C. Medeiros
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- affiliation: Pontifical Catholic University of Rio de Janeiro, Department of Economics, Brazil
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2020 – today
- 2023
[i5]Rafael Alves, Diego S. de Brito, Marcelo C. Medeiros, Ruy M. Ribeiro:
Forecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkage. CoRR abs/2303.16151 (2023)- 2021
- [i4]Marcelo C. Medeiros, Henrique F. Pires:
The Proper Use of Google Trends in Forecasting Models. CoRR abs/2104.03065 (2021) - 2020
- [i3]Jianqing Fan, Ricardo P. Masini, Marcelo C. Medeiros:
Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction. CoRR abs/2011.03996 (2020) - [i2]Ricardo P. Masini, Marcelo C. Medeiros, Eduardo F. Mendes
:
Machine Learning Advances for Time Series Forecasting. CoRR abs/2012.12802 (2020)
2010 – 2019
- 2018
- [j9]Yuri R. Fonseca, Ricardo M. Prates, Marcelo C. Medeiros, Gabriel F. R. Vasconcelos:
ArCo: An R package to Estimate Artificial Counterfactuals. R J. 10(1): 91 (2018) - [i1]Yuri R. Fonseca, Marcelo C. Medeiros, Gabriel F. R. Vasconcelos, Álvaro Veiga:
BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions. CoRR abs/1808.03698 (2018) - 2012
- [j8]Manabu Asai, Michael McAleer, Marcelo C. Medeiros:
Modelling and forecasting noisy realized volatility. Comput. Stat. Data Anal. 56(1): 217-230 (2012) - 2010
- [j7]José Luis Aznarte, Marcelo C. Medeiros, José Manuel Benítez:
Linearity testing for fuzzy rule-based models. Fuzzy Sets Syst. 161(13): 1836-1851 (2010) - [j6]José Luis Aznarte, Marcelo C. Medeiros, José Manuel Benítez:
Testing for Remaining Autocorrelation of the residuals in the Framework of Fuzzy Rule-Based Time Series Modelling. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(4): 371-387 (2010)
2000 – 2009
- 2008
- [j5]Joel Corrêa da Rosa, Álvaro Veiga, Marcelo C. Medeiros:
Tree-structured smooth transition regression models. Comput. Stat. Data Anal. 52(5): 2469-2488 (2008) - 2005
- [j4]Marcelo C. Medeiros, Álvaro Veiga:
A flexible coefficient smooth transition time series model. IEEE Trans. Neural Networks 16(1): 97-113 (2005) - 2001
- [j3]Marcelo C. Medeiros, Mauricio G. C. Resende, Álvaro Veiga:
Piecewise Linear Time Series Estimation with GRASP. Comput. Optim. Appl. 19(2): 127-144 (2001) - [j2]Marcelo C. Medeiros, Álvaro Veiga, Carlos Eduardo Pedreira:
Modeling exchange rates: smooth transitions, neural networks, and linear models. IEEE Trans. Neural Networks 12(4): 755-764 (2001) - 2000
- [j1]Marcelo C. Medeiros, Álvaro Veiga:
A hybrid linear-neural model for time series forecasting. IEEE Trans. Neural Networks Learn. Syst. 11(6): 1402-1412 (2000)
Coauthor Index
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