Hi:
I am using the package "KernSmooth" to do the local polynomial regression.
However, it seems the function "locpoly" can only deal with univariate
covaraite. I wonder is there any kernel smoothing package in R can deal with
bivariate covariates? I also checked the package "lcofit" in which function
"lcofit" can indeed deal with bivariate case. The code below is an example from
the its help document I found on http://www.locfit.info However, first, it is
a local regression method. I am not sure how to specify the degree of the
regression model. second, i dont know what are "scale" and "alpha". Are they
associated with the bandwidth?
Thanks very much!
data(ethanol)
# a bivariate local regression with smaller smoothing parameter
fit <- locfit(NOx~E+C, data=ethanol, scale=0, alpha=0.5)
plot(fit)
---------------------------------
[[alternative HTML version deleted]]
______________________________________________
[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
