Kernel Regression

Kernel Regression is one class of modeling methods that belongs to the smoothing methods family. Kernel Regression is used on longitudinal data, for example in finance. Other smoothing methods, related to time series analysis are available in the XLSTAT-Time module. Kernel regression does not take into account seasonalities, as the Holt-Winters method does, but it is able to take into account a set of explanatory variables. 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.