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.

中文翻译：

---

与能源生产有关的变量的半参数预测模型

在本文中，回顾了多年来在圣地亚哥德孔波斯特拉大学统计与运筹学系与位于西班牙阿科特蓬斯（西班牙科鲁尼亚）的发电厂的广泛合作下开发的半参数模型，这些发电厂是Endesa Generation的财产显示了SA。特别是，这些模型用于提前半小时预测该电站环境中的二氧化硫含量。本文还考虑了一种新的多维半参数模型。该模型是先前模型的概括，并考虑了误差的相关结构。在模拟研究中说明了其行为，并预测了电厂环境中两个重要污染指标的水平：