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)
 
			
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