Semiparametric Prediction Models for Variables Related with Energy Production

  • Wenceslao González-Manteiga
  • Manuel Febrero-Bande
  • María Piñeiro-Lamas
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 26)

Abstract

In this paper a review of semiparametric models developed throughout the years thanks to 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 sulfur 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 the prediction of the levels of two important pollution indicators in the environment of the power station: sulfur dioxide and nitrogen oxides.

Notes

Acknowledgements

The work by Wenceslao González-Manteiga and Manuel Febrero-Bande was partially supported by grants MTM2013-41383-P from Ministerio de Economía y Competitividad, Spain.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  • Wenceslao González-Manteiga
    • 1
  • Manuel Febrero-Bande
    • 1
  • María Piñeiro-Lamas
    • 2
  1. 1.Faculty of MathematicsUniversity of Santiago de CompostelaSantiago de CompostelaSpain
  2. 2.CIBER Epidemiología y Salud PúblicaComplexo Hospitalario da Universidade de SantiagoSantiago de CompostelaSpain

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