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
