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Prediction of SO 2 pollution incidents near a power station using partially linear models and an historical matrix of predictor‐response vectors
Author(s) -
PradaSánchez J. M.,
FebreroBande M.,
CotosYáñez T.,
GonzálezManteiga W.,
BermúdezCela J. L.,
LucasDomínguez T.
Publication year - 2000
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(200003/04)11:2<209::aid-env403>3.0.co;2-z
Subject(s) - linear regression , sampling (signal processing) , linear model , design matrix , statistics , environmental science , regression analysis , econometrics , term (time) , pollution , air pollution , power (physics) , meteorology , mathematics , computer science , geography , telecommunications , chemistry , thermodynamics , ecology , physics , organic chemistry , quantum mechanics , detector , biology
Atmospheric SO 2 concentrations at sampling stations near the fossil fuel fired power station at As Pontes (La Coruña, Spain) were predicted using a model for the corresponding time series consisting of a self‐explicative term and a linear combination of exogenous variables. In a supplementary simulation study, models of this kind behaved better than the corresponding pure self‐explicative or pure linear regression models. Copyright © 2000 John Wiley & Sons, Ltd.