RT Journal Article
T1 Semiparametric prediction models for variables related with energy production
A1 González Manteiga, Wenceslao
A1 Febrero Bande, Manuel
A1 Piñeiro Lamas, María
K1 Semiparametric prediction models
K1 Pollution indicators
K1 Cointegration
AB In this paper a review of semiparametric models developed throughout the years thanks to an extensive collaboration between the Department of Statistics and Operations Research of the University of Santiago de Compostela and a power station located in As Pontes (A Coruña, Spain) property of Endesa Generation, SA, is shown. In particular these models were used to predict the levels of sulphur dioxide in the environment of this power station with half an hour in advance. In this paper also a new multidimensional semiparametric model is considered. This model is a generalization of the previous models and takes into account the correlation structure of errors. Its behaviour is illustrated in a simulation study and with the prediction of the levels of two important pollution indicators in the environment of the power station: sulphur dioxide and nitrogen oxides.
PB SpringerOpen
SN 2190-5983
YR 2018
FD 2018
LK http://hdl.handle.net/10347/22129
UL http://hdl.handle.net/10347/22129
LA eng
NO González-Manteiga, W., Febrero-Bande, M. and Piñeiro-Lamas, M. Semiparametric prediction models for variables related with energy production. J.Math.Industry 8, 7 (2018). https://doi.org/10.1186/s13362-018-0049-0
NO The work by Wenceslao González-Manteiga and Manuel Febrero-Bande was partially supported by projectsMTM2013-41383-P and MTM2016-76969-P from the Spanish Ministry of Science and Innovation and European Regional Development Fund and IAP network StUDyS from Belgian Science Policy.
DS Minerva
RD 1 may 2026