Please do forget my questions as they are really trivial and I do not kno what I was thinking of.
Thank you thomas for clarifying my cloudy head today. jean, On Mon, 22 Sep 2003, Jean Eid wrote: > I am working with a model that I have to estimate a nonparametric > function. The model is partial linear i.e. > > Y=X$\beta$ + f(z) + $\epsilon$ > > I am using the ' double residual methods' Robinson (1988) Speckman (1988) > where I estimate a nonparametric function for each of the parametric > variables in terms of the nonparametric one i.e. > > X[,i]=g(Z)+ u > > this is done because I need the $E( X[,i]\vert Z)$ for each position j in > the vectors. > > the problem is that when I use the ksmooth() function in R it estimates > the function at different points and not those that consist of the Z > vector. > > the ksmooth() function in Splus on the other hand evaluates the points at > the corresponding Z vector. both codes are given below > > > d<-ksmooth(lprice,XX[,i],kernel="box") > unique(lprice-d$x) > > in SPLUS will generate 0 while in R it generates a vector of different > values. > > > > My second question is regarding the sm library: > > d<-sm.regression(lprice, XX[,i], h=sd(lprice), display="none") > will only generate 50 point estimates while NROW(XX[,i]) = 3897 > and when I do > d<-sm.regression(lprice, XX[,i], h=sd(lprice), display="none", > ngrid=NROW(lprice)) > > I get the right dimension of the estimated points but again they are not > estimated at the points in lprice. > > > Any help is greatly appreciated. > > P.S. I have Bowman and Azzalini book but unfortunately it does not clarify > the procedures in sm.regression() > > Jean, > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help