Choosing Quantile Regression Model Via Lasso Optimality for the Effect of the Salinity of Soil in Al-Shamia City-Iraq

Abstract

The variable selection is special case of model selection, choosing optimal model is considered hard mater, to overcome this problem lasso technique have been used. The quantile regression is a good tool for achieving evaluated the relationship between response variable and a set of explanatory variables because, it is effectiveness without assumptions. When built-in between the quantile regression and lasso technique give us a good method to achieving coefficient estimation and variable selection in different type regression models. To a choosing optimal model that show the variables more effected on earth salinity of AL-shamia city the lasso model selection in quantile regression model have been used .