Statistical Modelling and Variable Selection in Climate Science

Several modelling techniques are used in Statistics to obtain different models. The method of linear regression analysis is explained in this article. Several steps starting from concepts, calculation, and interpretation, which are involved in the modelling process are stepwise explained. The role of ridge regression for choosing important explanatory variable affecting the outcome is discussed and is used in the development of LASSO (least absolute shrinkage and selection operator) technique. How to find the linear regression model and the subset of important variables using LASSO with an open source R statistical software are illustrated.