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~person:"Medeiros, Marcelo C."
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Neuronale Netze
29
Neural networks
28
Zeitreihenanalyse
15
Theorie
14
Time series analysis
14
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13
Nichtlineare Regression
12
Prognoseverfahren
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11
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8
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nonlinear models
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Medeiros, Marcelo C.
Zenou, Yves
158
Nijkamp, Peter
91
Sabatini, Fabio
85
Fagiolo, Giorgio
82
Jackson, Matthew O.
56
Reggiani, Aura
54
Patacchini, Eleonora
49
Mauleon, Ana
48
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40
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38
Kapetanios, George
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Sarangi, Sudipta
36
Battiston, Stefano
35
Schiavo, Stefano
35
Vega-Redondo, Fernando
35
Feri, Francesco
33
Hellmann, Tim
33
König, Michael D.
33
Riccaboni, Massimo
32
Vannetelbosch, Vincent J.
32
Aldasoro, Iñaki
30
Lindner, Ines
30
Liu, Xiaodong
30
Sutter, Matthias
29
Cambini, Carlo
28
Dhillon, Amrita
28
Epstein, Gil S.
28
Verhoef, Erik T.
28
White, Halbert
28
Patuelli, Roberto
27
Claveria, Oscar
26
Fafchamps, Marcel
26
Pyka, Andreas
26
Sarracino, Francesco
26
Torra, Salvador
26
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25
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Pontifícia Universidade Católica do Rio de Janeiro / Departamento de Economia
3
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2
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1
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Texto para discussão / Pontifícia Universidade Católica do Rio de Janeiro, Departamento de Economia
8
International journal of forecasting
3
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2
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ECONIS (ZBW)
27
EconStor
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RePEc
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1
Global inflation: implications for forecasting and monetary policy
Medeiros, Marcelo C.
;
Montes Schütte, Erik Christian
; …
-
2023
Persistent link: https://www.econbiz.de/10014441020
Saved in:
2
Machine learning advances for time series forecasting
Masini, Ricardo P.
;
Medeiros, Marcelo C.
;
Mendes, Eduardo F.
- In:
Journal of economic surveys
37
(
2023
)
1
,
pp. 76-111
Persistent link: https://www.econbiz.de/10014287800
Saved in:
3
Machine learning advances for time series forecasting
Masini, Ricardo P.
;
Medeiros, Marcelo C.
;
Mendes, Eduardo F.
-
2020
networks
, in their feed-forward and recurrent versions, and tree-based methods, such as random forests and boosted trees. We …
Persistent link: https://www.econbiz.de/10012390030
Saved in:
4
Unobserved heterogeneity in regression models : a semiparametric approach based on nonlinear sieves
Assunção, Juliano J.
;
Burity, Priscila
;
Medeiros, …
- In:
Brazilian review of econometrics : BRE ; the review of …
35
(
2015
)
1
,
pp. 47-63
Persistent link: https://www.econbiz.de/10011538815
Saved in:
5
Machine learning advances for time series forecasting
Masini, Ricardo P.
;
Medeiros, Marcelo C.
;
Mendes, Eduardo F.
-
2020
networks
, in their feed-forward and recurrent versions, and tree-based methods, such as random forests and boosted trees. We …
Persistent link: https://www.econbiz.de/10012817069
Saved in:
6
A (semi)parametric functional coefficient logarithmic autoregressive conditional duration model
Fernandes, Marcelo
;
Medeiros, Marcelo C.
;
Veiga, Alvaro
- In:
Econometric reviews
35
(
2016
)
5/7
,
pp. 1221-1250
Persistent link: https://www.econbiz.de/10011591186
Saved in:
7
Forecasting realized volatility with linear and nonlinear models
McAleer, Michael
;
Medeiros, Marcelo C.
-
2010
In this paper we consider a nonlinear model based on neural
networks
as well as linear models to forecast the daily … ; volatility forecasting ; neural
networks
; nonlinear models ; realized volatility ; bagging …
Persistent link: https://www.econbiz.de/10003962167
Saved in:
8
Forecasting realized volatility with linear and nonlinear models
McAleer, Michael
;
Medeiros, Marcelo C.
-
2009
Persistent link: https://www.econbiz.de/10003910296
Saved in:
9
Forecasting Realized Volatility with Linear and Nonlinear Models
McAleer, Michael
-
2009
In this paper we consider a nonlinear model based on neural
networks
as well as linear models to forecast the daily …
Persistent link: https://www.econbiz.de/10013155198
Saved in:
10
Modeling and predicting the CBOE market volatility index
Fernandes, Marcelo
;
Medeiros, Marcelo C.
;
Scharth, Marcel
- In:
Journal of banking & finance
40
(
2014
),
pp. 1-10
Persistent link: https://www.econbiz.de/10010402334
Saved in:
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