The objective of the current study is to compare the performances of a classical regression method (SWR) and the LASSO technique for predictor selection. A data set from 9 stations located in the southern region of Quebec that includes 25 predictors measured over 29 years (from 1961 to 1990) is employed. The results indicate that, due to its computational advantages and its ease of implementation, the LASSO technique performs better than SWR and gives better results according to the determination coefficient and the RMSE as parameters forcomparison.

• Taesam Lee(Department of Civil Engineering Gyeongsang National University) Corresponding author
• Dorra Hammami(INRS-ETE, University of Quebec)
• TTaesam Lee(Water and Environmental Engineering, Masdar Institute of Science and Technology)
• Taha B. M. J. Ouarda(Stanford University)