RT Journal Article
T1 Predicting trace gas concentrations using quantile regression models
A1 Conde Amboage, Mercedes
A1 González Manteiga, Wenceslao
A1 Sánchez Sellero, César
K1 Quantile regression
K1 NOx concentration
K1 Prediction errors
K1 Prediction intervals
K1 Bootstrapping
K1 Median regression
AB Quantile regression methods are evaluated for computing predictions and prediction intervals of NOx concentrations measured in the vicinity of the power plant in As Pontes (Spain). For these data, smaller prediction errors were obtained using methods based on median regression compared with mean regression. A new method to construct prediction intervals involving median regression and bootstrapping the prediction error is proposed. This new method provides better coverage for NOx data compared with classical and bootstrap prediction intervals based on mean regression, as well as simpler prediction intervals based on quantile regression. A simulation study illustrates the features of this proposed method that lead to a better performance for obtaining prediction intervals for these particular NOx concentration data, as well as for any other environmental dataset that do not meet assumptions of homoscedasticity and normality of the error distribution
PB Springer
SN 1436-3240
YR 2017
FD 2017
LK http://hdl.handle.net/10347/18627
UL http://hdl.handle.net/10347/18627
LA eng
NO Conde-Amboage, M., González-Manteiga, W. & Sánchez-Sellero, C. Stoch Environ Res Risk Assess (2017) 31: 1359. https://doi.org/10.1007/s00477-016-1252-4
NO This is a post-peer-review, pre-copyedit version of an article published in Stoch Environ Res Risk Assess. The final authenticated version is available online at: https://doi.org/10.1007/s00477-016-1252-4
NO This study was supported by Project MTM2013-41383P from the Spanish Ministry of Economy and Competitiveness, as well as the European Regional Development Fund (ERDF). Support from the IAP network StUDyS from the Belgian Science Policy is also acknowledged. M. Conde-Amboage was supported by FPU grant AP2012-5047 from the Spanish Ministry of Education
DS Minerva
RD 23 abr 2026