Quantile regression: Theory and applications

In this study, Quantile Regression" method which was developed as an alternative to the least squares method " is discussed. Quantile Regression is the generalized version of Median regression for specified quantiles. This regression model is less sensitive to extreme values than the OLS models. The parameter estimation methods suggested in the literature are investigated for the Quantile regression method. The parameters of the regression model are estimated, the properties of these estimators are examined and compared with other estimators. The simulation study is carried out and the results are illustrated in data sets.Keywords: Least Squares Method, Least Absolute Deviation (LAD) Regression,Quantile Regression.