Comparison of several linear statistical models to predict tropospheric ozone concentrations

References

• Pires , J. C.M. , Sousa , S. I.V. , Pereira , M. C. , Alvim-Ferraz , M. C.M. and Martins , F. G. 2008 . Management of air quality monitoring using principal component and cluster analysis – Part II: CO, NO2 and O3 . Atmos. Environ. , 42 : 1261 – 1274 .
   Web of Science ®Google Scholar
• Guerra , J.-C. , Rodríguez , S. , Arencibia , M.-T. and García , M.-D. 2004 . Study on the formation and transport of ozone in relation to the air quality management and vegetation protection in Tenerife (Canary Islands) . Chemosphere , 56 : 1157 – 1167 .
   PubMed Web of Science ®Google Scholar
• Zolghadri , A. , Monsion , M. , Henry , D. , Marchionini , C. and Petrique , O. 2004 . Development of an operational model-based warning system for tropospheric ozone concentrations in Bordeaux, France . Environ. Modell. Softw. , 19 : 369 – 382 .
   Web of Science ®Google Scholar
• Dueñas , C. , Fernández , M. C. , Cañete , S. , Carretero , J. and Liger , E. 2002 . Assessment of ozone variations and meteorological effects in an urban area in the Mediterranean Coast . Sci. Total Environ. , 299 : 97 – 113 .
   PubMed Web of Science ®Google Scholar
• Lengyel , A. , Héberger , K. , Paksy , L. , Bánhidi , O. and Rajkó , R. 2004 . Prediction of ozone concentration in ambient air using multivariate methods . Chemosphere , 57 : 889 – 896 .
   PubMed Web of Science ®Google Scholar
• Sousa , S. I.V. , Pires , J. C.M. , Martins , F. G. , Pereira , M. C. and Alvim-Ferraz , M. C.M. 2009 . Potentialities of quantile regression to predict ozone concentrations . Environmetrics , 20 : 147 – 158 .
   Web of Science ®Google Scholar
• Agirre-Basurko , E. , Ibarra-Berastegi , G. and Madariaga , I. 2006 . Regression and multilayer perceptron-based models to forecast hourly O3and NO2levels in the Bilbao area . Environ. Modell. Softw. , 21 : 430 – 446 .
   Web of Science ®Google Scholar
• Pires , J. C.M. , Martins , F. G. , Sousa , S. I.V. , Alvim-Ferraz , M. C.M. and Pereira , M. C. 2008 . Selection and validation of parameters in multiple linear and principal component regressions . Environ. Modell. Softw. , 23 : 50 – 55 .
   Web of Science ®Google Scholar
• Sundberg , R. 2000 . Aspects of statistical regression in sensometrics . Food Qual. Prefer. , 11 : 17 – 26 .
   Web of Science ®Google Scholar
• Eberly , L. E. 2007 . “ Multiple linear regression ” . In Methods in Molecular Biology, Vol. 404: Topics in Biostatistics , Edited by: Ambrosius , W. T. 165 – 187 . Totowa : Humana Press Inc .
   Google Scholar
• Pires , J. C.M. , Sousa , S. I.V. , Pereira , M. C. , Alvim-Ferraz , M. C.M. and Martins , F. G. 2008 . Management of air quality monitoring using principal component and cluster analysis – Part I: SO2 and PM10 . Atmos. Environ. , 42 : 1249 – 1260 .
   Web of Science ®Google Scholar
• Çamdevýren , H. , Demýr , N. , Kanik , A. and Keskýn , S. 2005 . Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs . Ecol. Model. , 181 : 581 – 589 .
   Web of Science ®Google Scholar
• Harman , H. H. 1976 . Modern Factor Analysis , 3 , Chicago : University of Chicago Press .
   Google Scholar
• Hyvärinen , A. and Oja , E. 2000 . Independent component analysis: Algorithms and applications . Neural Netw. , 13 : 411 – 430 .
   PubMed Web of Science ®Google Scholar
• Abdi , H. 2003 . “ Partial least squares (PLS) regression ” . In Encyclopedia of Social Sciences Research Methods , Edited by: Lewis-Beck , M. , Bryman , A. and Futing , T. Thousand Oaks : Sage .
   Google Scholar
• Wold , S. , Sjöström , M. and Eriksson , L. 2001 . PLS-regression: A basic tool of chemometrics . Chemometr. Intell. Lab. , 58 : 109 – 130 .
   Web of Science ®Google Scholar
• Koenker , R. and Basset , G. 1978 . Regression quantiles . Econometrica , 46 : 33 – 50 .
   Web of Science ®Google Scholar
• Hayter , A. J. , Wynn , H. P. and Liu , W. 2005 . Slope modified confidence bands for a simple linear regression model . Stat. Methodol. , 3 : 186 – 192 .
   Google Scholar
• Gardner , M. W. and Dorling , S. R. 2000 . Statistical surface ozone models: An improved methodology to account for non-linear behaviour . Atmos. Environ. , 34 : 21 – 34 .
   Web of Science ®Google Scholar
• Pires , J. C.M. , Martins , F. G. , Sousa , S. I.V. , Alvim-Ferraz , M. C.M. and Pereira , M. C. 2008 . Prediction of the daily mean PM10concentrations using linear models . Am. J. Environ. Sci. , 4 : 445 – 453 .
   Google Scholar