Forecasting inflation in a data-rich environment: the benefits of machine learning methods MC Medeiros, GFR Vasconcelos, Á Veiga, E Zilberman Journal of Business & Economic Statistics 39 (1), 98-119, 2021 | 315 | 2021 |
Changes in the sedimentary organic carbon pool of a fertilized tropical estuary, Guanabara Bay, Brazil: an elemental, isotopic and molecular marker approach RS Carreira, ALR Wagener, JW Readman, TW Fileman, SA Macko, ... Marine Chemistry 79 (3-4), 207-227, 2002 | 222 | 2002 |
A hybrid linear-neural model for time series forecasting MC Medeiros, Á Veiga IEEE Transactions on Neural Networks 11 (6), 1402-1412, 2000 | 105 | 2000 |
A flexible coefficient smooth transition time series model MC Medeiros, Á Veiga IEEE transactions on neural networks 16 (1), 97-113, 2005 | 82 | 2005 |
Modeling exchange rates: smooth transitions, neural networks, and linear models MC Medeiros, Á Veiga, CE Pedreira IEEE Transactions on Neural Networks 12 (4), 755-764, 2001 | 80 | 2001 |
Modeling multiple regimes in financial volatility with a flexible coefficient GARCH (1, 1) model MC Medeiros, A Veiga Econometric Theory 25 (1), 117-161, 2009 | 76 | 2009 |
Second generation of “Miranda procedure” for violation <?format ?>in Dalitz studies of (and and ) decays I Bediaga, J Miranda, AC Dos Reis, II Bigi, A Gomes, ... Physical Review D—Particles, Fields, Gravitation, and Cosmology 86 (3), 036005, 2012 | 65 | 2012 |
Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics C Epprecht, D Guegan, Á Veiga, J Correa da Rosa Communications in Statistics-Simulation and Computation 50 (1), 103-122, 2021 | 60* | 2021 |
Diagnostic checking in a flexible nonlinear time series model MC Medeiros, A Veiga Journal of Time Series Analysis 24 (4), 461-482, 2003 | 49 | 2003 |
Validation of Ucides cordatus as a bioindicator of oil contamination and bioavailability in mangroves by evaluating sediment and crab PAH records AH Nudi, ALR Wagener, E Francioni, A de Lemos Scofield, CB Sette, ... Environment International 33 (3), 315-327, 2007 | 47 | 2007 |
Shewhart control charts for dispersion adjusted for parameter estimation R Goedhart, MM da Silva, M Schoonhoven, EK Epprecht, S Chakraborti, ... IISE Transactions 49 (8), 838-848, 2017 | 46 | 2017 |
Design of radial basis function network as classifier in face recognition using eigenfaces CE Thomaz, RQ Feitosa, Á Veiga Proceedings 5th Brazilian Symposium on Neural Networks (Cat. No. 98EX209 …, 1998 | 45 | 1998 |
Tree-structured smooth transition regression models JC Da Rosa, A Veiga, MC Medeiros Computational Statistics & Data Analysis 52 (5), 2469-2488, 2008 | 39 | 2008 |
PAR(p)-vine copula based model for stochastic streamflow scenario generation G Pereira, Á Veiga Stochastic environmental research and risk assessment 32, 833-842, 2018 | 33 | 2018 |
Asset liability management for open pension schemes using multistage stochastic programming under Solvency-II-based regulatory constraints TB Duarte, DM Valladão, Á Veiga Insurance: Mathematics and Economics 77, 177-188, 2017 | 32 | 2017 |
Otimização de entropia: implementação computacional dos princípios Maxent e Minxent RS Mattos, Á Veiga Pesquisa Operacional 22, 37-59, 2002 | 32 | 2002 |
Fostering wind power penetration into the Brazilian forward-contract market A Street, DA Lima, Á Veiga, B Fânzeres, L Freire, B Amaral 2012 IEEE Power and Energy Society General Meeting, 1-8, 2012 | 30 | 2012 |
A combinatorial approach to piecewise linear time series analysis MC Medeiros, A Veiga, MGC Resende Journal of Computational and graphical Statistics 11 (1), 236-258, 2002 | 28 | 2002 |
Revisiting hydrocarbons source appraisal in sediments exposed to multiple inputs CG Massone, A de LR Wagener, HM de Abreu, Á Veiga Marine pollution bulletin 73 (1), 345-354, 2013 | 26 | 2013 |
Risk constrained contracting strategies of renewable portfolios F Ralston, S Granville, M Pereira, LA Barroso, A Veiga 2010 7th International Conference on the European Energy Market, 1-7, 2010 | 26 | 2010 |