After a short introduction to topics in nonparametric curve estimation, covered in my new 2018 Chapman & Hall’s book with the same title as the talk, three specific problems will be considered. The first one is nonparametric regression with missing at random (MAR) responses. It will be explained that a complete case approach is optimal in this case. The second problem is nonparametric regression with missing at random (MAR) predictors. It will be explained that in general a complete case approach is inconsistent for this type of missing and a special procedure is needed for efficient estimation. The last explored problem is devoted to estimation of hazard rate functions for truncated and censored data.