We study the problem of estimating conditional distribution functions from data containing additional errors. The only assumption on these errors is that a weighted sum of the absolute errors tends to zero with probability one for sample size tending to infinity. We prove sufficient conditions...

Let (X,Y) be a pair of random variables with supp(X) \subseteq [0,1]?I and EY?2 \infinity. Let m* be the best approximation of the regression function of (X,Y) by sums of functions of at most d variables (formula). Estimation of m* from i.i.d. data is considered. For the estimation interaction...