Approximation: Nadaraya Watson kernel regression

We calculate

where

for

Here, we set Gaussian kernel(pdf standard normal) to K( ) for example.

As bandwidth h increases, the resulting curve will be stretched out.

If h increases too much, it deviates from the local points and it is going to be linear

globally. The best fit is around h=0.05 in the case above.