Dear Sir, Madam, or to whom this may concern,
my name is Jan Failenschmid and I am a Ph.D. student at Tilburg University.
For my project I have been looking into different types of kernel regression
estimators and corresponding R functions.
While comparing different functions I noticed that stats::ksmooth returned
different estimates for the same bandwidth
as other kernel regression estimators that should be equivalent (i.e. the local
polynomial estimators KernSmooth::locpoly and
locpol::locpol with degree 0). However, when optimizing the bandwidth of
ksmooth separately using the same loss function, I find comparable estimates to
the other two estimators for a (larger) different bandwidth. To confirm this, I
wrote my own Nadaraya-Watson kernel regression estimator, which is consistent
with the two local polynomial estimators and shows the same discordance with
ksmooth.
This led me to the suspicion that the bandwidth that is passed to kmooth is
rescaled or transformed within the function. Unfortunately, I was not able to
confirm this with either the code of the function or the documentation. It
would be of great help to me if you could clarify this for me.
Thank you very much for your time and help in advance.
Kind regards,
Jan Failenschmid
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