> From: Matt Hart > > Thanks. Yes, I think this is right. As I understand it S-G > does a local > unweighted polynomial regression. I think other smoothers > already weigh > the data by the distance from the estimation point. I'm not sure what > happens when you mix the two...
Makes perfect sense to statisticians. The two sets of weights are for different reasons. The distance weights (kernels) are for smoothness and bias/variance properties of the estimates. Andy > m. > > Liaw, Andy wrote: > > >If I'm not mistaken, S-G is essentially a local > (even-degree) polynomial > >smoother with constant bandwidth. You can use a constant > bandwidth local > >polynomial smoother that allows weights; e.g., in the locfit package. > > > >HTH, > >Andy > > > > > > > >>From: Matt Hart > >> > >>Hi, > >> > >>Does anyone know how to use weights and generate error bounds for > >>Savitzky-Golay? I have a (smallish) set of points y equally > >>spaced each > >>with a known error and would like to smooth them using S-G > >>but so as to > >>take into account the error already have and construct new > >>error bounds > >>around them that take into account the errors they had at the > >>beginning > >>and the erros they get as a result of the smoothing. > >> > >>thanks, m. > >> > >>______________________________________________ > >>[EMAIL PROTECTED] mailing list > >>https://stat.ethz.ch/mailman/listinfo/r-help > >>PLEASE do read the posting guide! > >>http://www.R-project.org/posting-guide.html > >> > >> > >> > >> > > > >______________________________________________ > >[EMAIL PROTECTED] mailing list > >https://stat.ethz.ch/mailman/listinfo/r-help > >PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > > > > > > ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
