Kernel Regression is one class of modeling methods that belongs to the smoothing methods family. It is part of the non paremetric regression methods. Kernel regression allows you to base the prediction of a value on passed observations, and to weight the impact of passed observations depending on how similar they are compared with the current values of the explanatory variables. Lowess and robust Lowess regression methods are also available.