I have a set of estimates of function values, along with estimates of their standard errors. To somewhat simplify matters: for $x$ running from $1$ up to $70$ in (integer) steps (in fact a parameter in model selection), I have an estimate of the matching $y$-value (in fact an AUC) and an estimate of its SE. I cannot make assumptions on the form of the curve (it's not even certain that it's unimodal, for example), other than that it should be smooth on the scale of my $x$ values.
I am looking for a way to translate these to a more smooth form, because the method I am using tends to create the occasional spike that I hope to circumvent.
Now, most smoothing algorithms only use the $y$ values, which, in this case, seems to be a waste of information (i.e. not using the SE). In addition, I would also like to smooth out an error band from the error flags.
Somewhat to my surprise, I have not found a technique that provides this. Have I not looked well enough? I would also like to perform this in R, so if anybody has a package that does the trick, I'd be very happy.