For each point in a vector, the LOESS smoothing method fits a 0th/1st/2nd degree polynomial through that point and its alpha nearest neighbours. However, it is not easily documented what the function stats::loess does with points at the start and end of a vector: does it simply include fewer points in the polynomial fit? Does it still include alpha points, but no longer symmetrically distributed around the point of interest (my vector is evenly spaced)? Does it "mirror" the points, like the savgol filter in scipy can do?
Any help would be greatly appreciated!