Missing and Modified Data in Nonparametric Estimation

Focusing on nonparametric curve estimation, this book addresses challenges posed by missing and modified data, including scenarios of missing at random and not at random, as well as issues like truncation, censoring, and measurement errors commonly found in survival analysis. It introduces a universal nonparametric series E-estimator, grounded in the concept of estimating a population mean from a sample mean. The straightforward methodology is supported by asymptotic theory, demonstrating the E-estimator's superiority over other estimators.