Title: Missing and Modified Data in Nonparametric Statistics
Abstract: After a short introduction to topics in nonparametric curve estimation, covered in my new 2018 Chapman & Hall book with the same title as the talk, three specific problems will be considered. The first one is non-parametric 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 a 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 survival analysis, specifically to efficient estimation of a hazard rate function for truncated and censored data. Time permitted, several recent results and open problems will be highlighted.
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