I am attempting to find a reference which explains how one computes standard errors for local polynomial regression? Specifically, in R one can use the loess function to get a model object and then use the predict function to retrieve standard errors. Is there a reference somewhere to what is actually happening? What about in the case when there may be serial correlation in the residuals, one must adjust this using Newey-West type methods, is there a way to use the sandwich package to do this as you would for a regular OLS using lm?
I tried looking at the source but the standard error computation calls a C function.