Closed dmarx closed 1 year ago
semi-lowess lerping:
rationale here is leverage lowess smoothing while forcing function to take defined values where we have them.
as I've got it, I think this algorithm actually produces a sharp corner at d/2, which I definitely don't want.
the interpolator I'm looking for definitely exists already, I need to not reinvent the wheel here.
way simpler: just use an interpolation method that requires a context of two observations per endpoint instead of one, e.g. cubic, hermitian, catmull-rom - http://paulbourke.net/miscellaneous/interpolation/
maybe later...
https://en.wikipedia.org/wiki/Local_regression
tri-cube and gaussian kernels