Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling
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- Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003. "Local-global neural networks: a new approach for nonlinear time series modelling," Textos para discussão 470, Department of Economics PUC-Rio (Brazil).
References listed on IDEAS
- Potscher, Benedikt M. & Prucha, Ingmar R., 1986. "A class of partially adaptive one-step m-estimators for the non-linear regression model with dependent observations," Journal of Econometrics, Elsevier, vol. 32(2), pages 219-251, July.
- Yao, Qiwei & Tong, Howell, 1994. "On subset selection in non-parametric stochastic regression," LSE Research Online Documents on Economics 6409, London School of Economics and Political Science, LSE Library.
- Rong Chen, 1995. "Threshold Variable Selection In Open‐Loop Threshold Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(5), pages 461-481, September.
- White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-161, January.
- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999.
"A simple variable selection technique for nonlinear models,"
SSE/EFI Working Paper Series in Economics and Finance
296, Stockholm School of Economics, revised 06 Apr 2000.
- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SFB 373 Discussion Papers 1999,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," Finance 9904005, University Library of Munich, Germany.
- Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006.
"Building neural network models for time series: a statistical approach,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
- Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," SSE/EFI Working Paper Series in Economics and Finance 508, Stockholm School of Economics.
- Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002. "Building Neural Network Models for Time Series: A Statistical Approach," Textos para discussão 461, Department of Economics PUC-Rio (Brazil).
- Stephen Leybourne & Paul Newbold & Dimitrios Vougas, 1998. "Unit roots and smooth transitions," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(1), pages 83-97, January.
- Lai T.L. & Po-Shing Wong S., 2001. "Stochastic Neural Networks With Applications to Nonlinear Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 968-981, September.
- Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
- Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
Citations
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- Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
- Areosa, Waldyr Dutra & McAleer, Michael & Medeiros, Marcelo C., 2011.
"Moment-based estimation of smooth transition regression models with endogenous variables,"
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- Areosa, W.D. & McAleer, M.J. & Medeiros, M.C., 2008. "Moment-bases estimation of smooth transition regression models with endogenous variables," Econometric Institute Research Papers EI 2008-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Waldyr Dutra Areosa & Michael McAleer & Marcelo Cunha Medeiros, 2010. "Moment-based estimation of smooth transition regression models with endogenous variables," Textos para discussão 571, Department of Economics PUC-Rio (Brazil).
- Waldyr Dutra Areosa & Michael McAleer & Marcelo C. Medeiros, 2009. "Moment-Based Estimation of Smooth Transition Regression Models with Endogenous Variables," CIRJE F-Series CIRJE-F-671, CIRJE, Faculty of Economics, University of Tokyo.
- José Luis Aznarte & Marcelo Cunha Medeiros & José Manuel Benítez Sánchez, 2010. "Linearity Testing Against a Fuzzy Rule-based Model," Textos para discussão 566, Department of Economics PUC-Rio (Brazil).
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023.
"Machine learning advances for time series forecasting,"
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- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
- Marcelo Fernandes & Marcelo Cunha Medeiros & Alvaro Veiga, 2006.
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- Fernandes, Marcelo & Medeiros, Marcelo C. & Veiga, Alvaro, 2013. "A (semi-)parametric functional coefficient autoregressive conditional duration model," Textos para discussão 343, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
- Felix Chan & Michael McAleer & Marcelo C. Medeiros, 2015.
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Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 16(1), pages 1-21.
- Felix Chan & Michael McAleer & Marcelo C. Medeiros, 2010. "Structure and Asymptotic Theory for Nonlinear Models with GARCH Errors," Working Papers in Economics 10/79, University of Canterbury, Department of Economics and Finance.
- Felix Chan & Michael McAleer & Marcelo C. Medeiros, 2010. "Structure and Asymptotic Theory for Nonlinear Models with GARCH Errors," KIER Working Papers 754, Kyoto University, Institute of Economic Research.
- Chan, F. & McAleer, M.J. & Medeiros, M.C., 2011. "Structure and Asymptotic theory for Nonlinear Models with GARCH Errors," Econometric Institute Research Papers EI 2010-79, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Stockis, Jean-Pierre & Tadjuidje-Kamgaing, Joseph & Franke, Jürgen, 2008. "A note on the identifiability of the conditional expectation for the mixtures of neural networks," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 739-742, April.
- McAleer, Michael & Medeiros, Marcelo C., 2008.
"A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries,"
Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
- Michael McAller & Marcelo C. Medeiros, 2007. "A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries," Textos para discussão 544, Department of Economics PUC-Rio (Brazil).
- Hillebrand Eric & Medeiros Marcelo C. & Xu Junyue, 2013.
"Asymptotic Theory for Regressions with Smoothly Changing Parameters,"
Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 133-162, April.
- Eric Hillebrand & Marcelo C. Medeiros & Junyue Xu, 2012. "Asymptotic Theory for Regressions with Smoothly Changing Parameters," CREATES Research Papers 2012-31, Department of Economics and Business Economics, Aarhus University.
- Medeiros, Marcelo C & Magri, Rafael, 2013. "Nonlinear Error Correction Models With an Application to Commodity Prices," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(2), November.
- Marcelo Cunha Medeiros & Felix Chan & Michael McAller, 2005. "Structure and asymptotic theory for STAR(1)-GARCH(1,1) models," Textos para discussão 506, Department of Economics PUC-Rio (Brazil).
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