Apologies in advance if my comments don't help, in which case, no need to respond, but I noted in ?ksmooth:
"bandwidth the bandwidth. The kernels are scaled so that their quartiles (viewed as probability densities) are at ± 0.25*bandwidth." So, could this be a source of the discrepancies you cited? Given that ?ksmooth explicitly says: "Note: This function was implemented for compatibility with S, although it is nowhere near as slow as the S function. Better kernel smoothers are available in other packages such as KernSmooth." One wonder why you bother with it at all? (That was rhetorical -- do not answer). Cheers, Bert On Thu, Oct 26, 2023 at 11:06 AM Jan Failenschmid via R-help <r-help@r-project.org> wrote: > > 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 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
