Sam Efromovich: Missing and Modified Data in Nonparametric Estimation
Time: Wed 2019-05-15 13.00 - 14.00
Location: Room B705, Department of Statistics, Stockholm University
Participating: Sam Efromovich, University of Texas at Dallas
After a short introduction to topics in nonparametric curve estimation, covered in my new Chapman & Hall 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 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 third problem is devoted to survival analysis, specifically to efficient estimation of the hazard rate function for truncated and censored data. Time permitted, several recent results and open problems will be highlighted.